CN109636002B - Cold chain logistics distribution center site selection method and system based on goods loss - Google Patents
Cold chain logistics distribution center site selection method and system based on goods loss Download PDFInfo
- Publication number
- CN109636002B CN109636002B CN201811348120.5A CN201811348120A CN109636002B CN 109636002 B CN109636002 B CN 109636002B CN 201811348120 A CN201811348120 A CN 201811348120A CN 109636002 B CN109636002 B CN 109636002B
- Authority
- CN
- China
- Prior art keywords
- distribution center
- cost
- goods
- logistics
- transportation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000010187 selection method Methods 0.000 title description 3
- 238000009826 distribution Methods 0.000 claims abstract description 47
- 238000000034 method Methods 0.000 claims abstract description 30
- 238000013178 mathematical model Methods 0.000 claims abstract description 8
- 238000004321 preservation Methods 0.000 claims description 27
- 238000005057 refrigeration Methods 0.000 claims description 24
- 238000010276 construction Methods 0.000 claims description 15
- 238000005265 energy consumption Methods 0.000 claims description 14
- 238000009413 insulation Methods 0.000 claims description 13
- 238000004458 analytical method Methods 0.000 claims description 9
- 238000007726 management method Methods 0.000 claims description 9
- 235000013305 food Nutrition 0.000 claims description 8
- 238000010206 sensitivity analysis Methods 0.000 claims description 7
- 238000012795 verification Methods 0.000 claims description 7
- 238000012423 maintenance Methods 0.000 claims description 4
- 238000004519 manufacturing process Methods 0.000 claims description 4
- 239000000463 material Substances 0.000 claims description 4
- 230000008569 process Effects 0.000 abstract description 7
- 238000003860 storage Methods 0.000 description 6
- 230000008859 change Effects 0.000 description 3
- 230000007423 decrease Effects 0.000 description 3
- 238000002844 melting Methods 0.000 description 3
- 230000008018 melting Effects 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000001816 cooling Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000011534 incubation Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000000155 melt Substances 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000012856 packing Methods 0.000 description 1
- 235000014102 seafood Nutrition 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 235000013311 vegetables Nutrition 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/043—Optimisation of two dimensional placement, e.g. cutting of clothes or wood
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method and a system for selecting a site of a cold chain logistics distribution center based on goods loss, wherein the method comprises the following steps: selecting a plurality of addresses in a target area as alternative points of a distribution center; determining the transportation conditions from the suppliers to the distribution centers and from the distribution centers to the demand points; determining the cost of goods loss according to the transportation condition, inputting the total cost of logistics including the cost of goods loss into a mathematical model, and constructing an address selection model on the condition that the total cost of logistics is lower than a preset value; and solving the site selection model by using simulation software, and outputting the site selection result of the distribution center. The invention constructs an addressing model with the aim of minimizing the total logistics cost based on the transportation condition of goods and taking the goods loss cost into consideration, so that the addressing of the cold-chain logistics distribution center is more real and reasonable, the optimal address can be selected for the distribution center, and the cost of the whole logistics process is reduced.
Description
Technical Field
The invention relates to the technical field of site selection of logistics distribution centers, in particular to a site selection method and system of a cold chain logistics distribution center based on goods loss.
Background
In recent years, the national cold chain logistics industry develops rapidly, and the growth rate of 25% of the annual average is maintained. At present, the construction of the cold chain in China is very imperfect, the third party cold chain logistics is still undeveloped, the cold chain distribution level is not high, the logistics cost of agricultural products and fresh products is relatively high, the cost of the agricultural products and the fresh products is more than 40% of the unit price of fresh electric suppliers at present, and the profit break of the fresh electric suppliers is made. The related statistical data show that the cold chain circulation rate of China is low, the foundation is weak, the average cold chain rate is less than 1/5 of developed countries, the loss rate of goods is more than 4 times of that of the developed countries, the capacity of a per capita cold storage is only 1/4 of that of the United states, the proportion of refrigerated vehicles to freight vehicles is only about 0.3%, and the proportion is far behind 1% -3% of that of the developed countries. Meanwhile, the layout of the traditional cold chain logistics distribution center in China has a plurality of problems, and the circulation speed and quality of fresh products are greatly influenced. The reasonable location of the cold chain logistics distribution center is important to improve the logistics current situation and control the logistics distribution cost. Therefore, the problem of cold chain logistics distribution center site selection becomes a research hotspot in recent years.
While more and more students at home and abroad have begun to develop cold chain logistics related studies and have achieved some results in cold chain logistics distribution center site selection studies, the current cold chain logistics distribution center site selection studies are mainly focused on transportation cost, distribution timeliness and customer service level. There is still a lack of research on food loss, and in cold chain logistics, food loss has a close relationship with the site selection of the distribution center, and unreasonable site selection will directly increase the food loss condition.
Accordingly, the prior art is still in need of improvement and development.
Disclosure of Invention
The invention aims to solve the technical problem that the defects in the prior art are overcome, and provides a method and a system for selecting the site of a cold chain logistics distribution center based on the goods loss, which aims to solve the problem that the goods loss is not considered in the site selection of the cold chain logistics distribution center in the prior art.
The technical scheme adopted for solving the technical problems is as follows:
a method of locating a cold chain logistics distribution center based on a loss of goods, wherein the method comprises:
selecting a plurality of addresses in a target area as alternative points of a distribution center;
determining the transportation conditions from the suppliers to the distribution centers and from the distribution centers to the demand points;
determining the cost of goods loss according to the transportation condition, inputting the total cost of logistics including the cost of goods loss into a mathematical model, and constructing an address selection model on the condition that the total cost of logistics is lower than a preset value;
and solving the site selection model by using simulation software, and outputting the site selection result of the distribution center.
The method for selecting the site of the cold chain logistics distribution center based on the goods loss, wherein the method further comprises the following steps:
and verifying and analyzing the site selection model by using simulation software, and analyzing the influence of each parameter in the site selection model on the site selection result of the distribution center and the total cost of the logistics.
The method for selecting the site of the cold chain logistics distribution center based on the goods loss, wherein the transportation conditions comprise: cooling energy consumption of the transport vehicle from the supplier to the respective distribution center, and insulation time in the insulation can during the distribution phase.
The method for selecting the site of the cold chain logistics distribution center based on the goods loss, wherein the goods loss cost needs to consider the rate of goods spoilage; the rate of spoilage of the goods is related to the hold time in the incubator during the dispensing phase.
The method for selecting the site of the cold chain logistics distribution center based on the goods loss, wherein the total logistics cost comprises the following steps: transportation cost, refrigeration energy consumption of transportation vehicle quantity, food and goods loss cost, heat preservation ice bag refrigeration cost, distribution center warehouse management cost, distribution center construction cost and warehouse refrigeration cost.
According to the method for selecting the address of the cold chain logistics distribution center based on the goods loss, the address selecting model is a 0-1 integer nonlinear programming model.
The method for selecting the address of the cold chain logistics distribution center based on the goods loss comprises the following steps:
wherein,
x ij ≥0,y jk ≥0,i＝1,2,3...M；j＝1,2,3...N；k＝1,2,3...P (11)
l jk =0 or 1, z j =0 or 1, j=1..n (12);
formula (1) indicates that the weight of goods from supplier i to each distribution center is within its production capacity; formula (2) represents a capacity limitation of the distribution center; equation (3) represents the customer demand amount at which the supply amount of each distribution center satisfies the demand point k; formula (4) represents that the goods received by each distribution center are equal to the goods sent out; formula (5) represents ensuring that at least one distribution center is established; equation (6) indicates that the number of established distribution centers cannot exceed p; equation (7) shows that each customer is only supplied by one distribution center; formula (8) shows that the distribution center has certain corresponding distribution clients, and the condition that the logistics distribution center is selected and no clients exist; the formulas (9) and (10) represent the relationship between the transport capacity and the alternative point; the formulas (11) and (12) represent constraints on the values of the parameters;
wherein Q represents the total cost of the material flow; m represents the number of suppliers; n represents the number of alternative distribution centers; p represents the number of demand points; x is x ij Representing the traffic of supplier i to distribution center j; y is jk Representing the traffic volume from the delivery point j to the demand point k; h represents the unit transportation cost in the transportation stage; h' represents the unit transportation cost in the delivery stage; r is (r) ij Representing the distance from supplier i to delivery point j; s is(s) jk Representing the distance from the distribution center j to the demand point k; a is that i Representing the capacity of supplier i; o (o) j A delivery upper limit indicating the delivery center j; d (D) k Representing customer demand for demand point k; v denotes a fixed vehicle speed from the supplier to the distribution center; v' represents a fixed vehicle speed from the distribution center to the demand point; a represents the rated cargo capacity of the large transport vehicle; b represents the capacity of the preservation box in the delivery stage; d represents the cost of a fresh box; w represents the vehicle refrigeration energy consumption cost per unit time in the transportation stage; q fresh represents the unit price of fresh product; c represents the fixed maintenance cost of the distribution center; g j Representing the unit management cost of the warehouse j to the goods; f (f) j Representing warehouse construction costs; z j Expressed as an integer variable from 0 to 1; l (L) jk Indicating whether the distribution line is selected; l represents a sufficiently large number.
The method for selecting the address of the cold chain logistics distribution center based on the goods loss comprises the steps of verifying and analyzing the address selection model by using simulation software, and analyzing the influence of each parameter in the address selection model on the address selection result of the distribution center and the total logistics cost, wherein the method comprises the following steps:
and carrying out sensitivity analysis on the spoilage rate coefficient, the customer demand, the transportation vehicle-mounted goods quantity and the heat preservation time in the heat preservation box in the delivery stage in the site selection model by using simulation software to obtain the influence of the spoilage rate coefficient, the customer demand, the transportation vehicle-mounted goods quantity and the heat preservation time in the heat preservation box in the delivery stage on site selection results and logistics total cost.
A system for locating a cold chain logistics distribution center based on any one of the above, wherein the system comprises:
the alternative point selection module is used for selecting a plurality of addresses in the target area as alternative points of the distribution center;
the transportation condition determining module is used for determining transportation conditions from the suppliers to the distribution centers and from the distribution centers to the demand points;
the site selection model construction module is used for determining the cargo loss cost according to the transportation condition, inputting the logistics total cost including the cargo loss cost into the mathematical model, and constructing the site selection model under the condition that the logistics total cost is minimum;
and the address selection result output module is used for solving the address selection model by using simulation software and outputting the address selection result of the distribution center.
The system for selecting the site of the cold chain logistics distribution center based on the goods loss, wherein the system further comprises:
and the verification analysis module is used for carrying out verification analysis on the site selection model by using simulation software and analyzing the influence of each parameter in the site selection model on the site selection result of the distribution center and the total cost of the logistics.
The invention has the beneficial effects that: the invention constructs an addressing model with the aim of minimizing the total logistics cost based on the transportation condition of goods and taking the goods loss cost into consideration, so that the addressing of the cold-chain logistics distribution center is more real and reasonable, the optimal address can be selected for the distribution center, and the cost of the whole logistics process is reduced.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of the method for locating a cold chain logistics distribution center based on cargo loss.
Fig. 2 is a schematic block diagram of the system for locating a cold chain logistics distribution center based on cargo loss of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clear and clear, the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment provides a method for selecting a site of a cold chain logistics distribution center based on goods loss, as shown in fig. 1, the method comprises the following steps:
step S100, selecting a plurality of addresses in a target area as alternative points of a distribution center;
step 200, determining the transportation conditions from the suppliers to each distribution center and from each distribution center to each demand point;
step S300, determining the cost of goods loss according to the transportation condition, inputting the total cost of logistics including the cost of goods loss into a mathematical model, and constructing an address selection model on the condition that the total cost of logistics is lower than a preset value;
and step 400, solving the addressing model by using simulation software, and outputting an addressing result of the distribution center.
The network of cold chain streams is typically divided into three stages, including several suppliers, distribution centers, and points of demand. The fresh products are pre-cooled in a refrigerator nearby a supplier, then are transported in a long-distance refrigeration way to a distribution center through a large-sized refrigerator car, and are refrigerated and distributed to a demand point by the distribution center after being processed and transferred in the distribution center. Because the fresh products of different categories have different requirements on storage, transportation, such as temperature, humidity, time and the like, the invention only researches and constructs a cold chain logistics network for the fresh products of certain categories. The following problems are mainly considered in the construction of the cold chain logistics network: how to determine the number and location of distribution centers, and the amount of transport of suppliers to distribution centers, distribution centers to demand, minimizes the total cost of the stream for cold chain stream operation. Here, the total logistic cost of the logistic operation includes the construction cost and the transfer cost of the distribution center, the refrigeration cost of the transportation and distribution process, and the transportation cost and the goods loss cost of the fresh products. Meanwhile, when a logistics network of fresh products is constructed, factors such as the supply capacity of suppliers, the product requirements of markets, the storage capacity of distribution centers and the like are considered. It can be seen that the location of distribution centers in a cold chain logistics network is closely related to a number of factors.
Specifically, in this embodiment, a plurality of addresses are first selected on a map of a target area as candidate points of a distribution center, and if the transportation conditions are relatively good during the transportation link of fresh product cargoes, the damage of the cargoes is relatively less, and the current damage of the cargoes mainly occurs in the distribution link. It is therefore necessary in this embodiment to determine the conditions of transportation of the suppliers to the respective distribution centers and the respective distribution centers to the respective demand points. Preferably, the transportation conditions mainly include: cooling energy consumption of the transport vehicle from the supplier to the respective distribution center, and insulation time in the insulation can during the distribution phase. After the knowledge of the transport conditions is determined, the damage to the goods during the transport and delivery process can be determined, and thus the cost of the damage to the goods can be determined.
In this embodiment, the cost of the loss of goods requires consideration of the rate of spoilage of the goods; the rate of spoilage of the goods is related to the hold time in the incubator during the dispensing phase. In particular, since the spoiled parts of the fresh product have an influence on other intact parts during the storage and transportation process, the fresh product is transportedThe storage and transportation time is increased, the rate of goods decay is faster and faster, and the rate of decay is exponentially increased. In the study of problems in fresh product cold chain transportation, arrhenius Wu Sigong (Arrhenius equation) is generally used to represent the spoilage rate of goods as follows: q (t) =q 0 e -θt ，
Wherein Q is 0 Is the quality of the initial cargo when it has not been spoiled, Q (t) is the quality of the cargo at time t, and θ represents the spoiling rate coefficient of the cargo during transportation.
Furthermore, due to certain heat preservation measures in the delivery link, no goods loss can be generated in the earlier stage. However, over time, the ice in the incubator melts and the cargo spoils. Therefore, in order to more accurately represent the spoilage of the goods, it is assumed in the present embodiment that the time for melting the ice cubes in the incubator during the dispensing stage is t' (incubation time). The decay rate coefficient θ is considered in sections, such as:
according to the formula, when the time t of cargo transportation is within the time t' of melting ice cubes in the heat insulation box, the spoilage rate coefficient theta of the cargo is 0, namely the cargo is not spoiled basically. When the time t of cargo transportation is greater than the time t' of melting ice cubes in the heat insulation box, the factor theta of the spoilage rate of the cargo is a, and according to the formula of the spoilage rate, obvious spoilage of the cargo can occur, and the spoilage degree can be more serious as time goes back.
The embodiment obtains the cargo damage condition of the cargo based on the spoilage rate of the cargo, and obtains the cargo damage cost. And the cost of goods loss is also taken into consideration when constructing the site selection model, so that a more reasonable site selection model is constructed.
Further, the site selection model in the implementation is constructed on the condition that the total cost of the logistics is lower than a preset value. Preferably, in practical application, the model is constructed by adopting the condition of lowest total cost of logistics. In addition to the cost of goods loss, the total cost of the logistics further comprises: transportation cost, refrigeration energy consumption of transportation vehicle quantity, food and goods loss cost, heat preservation ice bag refrigeration cost, distribution center warehouse management cost, distribution center construction cost and warehouse refrigeration cost.
The site selection model constructed in this embodiment is:
wherein,
x ij ≥0,y jk ≥0,i＝1,2,3...M；j＝1,2,3...N；k＝1,2,3...P (11)
l jk =0 or 1, z j =0 or 1, j=1..n (12);
formula (1) indicates that the weight of goods from supplier i to each distribution center is within its production capacity; formula (2) represents a capacity limitation of the distribution center; equation (3) represents the customer demand amount at which the supply amount of each distribution center satisfies the demand point k; formula (4) represents that the goods received by each distribution center are equal to the goods sent out; formula (5) represents ensuring that at least one distribution center is established; equation (6) indicates that the number of established distribution centers cannot exceed p; equation (7) shows that each customer is only supplied by one distribution center; formula (8) shows that the distribution center has certain corresponding distribution clients, and the condition that the logistics distribution center is selected and no clients exist; the formulas (9) and (10) represent the relationship between the transport capacity and the alternative point; the formulas (11) and (12) represent constraints on the values of the parameters;
wherein Q represents the total cost of the material flow; m represents the number of suppliers; n represents the number of alternative distribution centers; p represents the number of demand points; x is x ij Representing the traffic of supplier i to distribution center j; y is jk Representing the traffic volume from the delivery point j to the demand point k; h represents the unit transportation cost in the transportation stage; h' represents the unit transportation cost in the delivery stage; r is (r) ij Representing the distance from supplier i to delivery point j; s is(s) jk Representing the distance from the distribution center j to the demand point k; a is that i Representing the capacity of supplier i; o (o) j A delivery upper limit indicating the delivery center j; d (D) k Representing customer demand for demand point k; v denotes a fixed vehicle speed from the supplier to the distribution center; v' represents a fixed vehicle speed from the distribution center to the demand point; a represents a large transport vehicleRated cargo capacity; b represents the capacity of the preservation box in the delivery stage; d represents the cost of a fresh box; w represents the vehicle refrigeration energy consumption cost per unit time in the transportation stage; q fresh represents the unit price of fresh product; c represents the fixed maintenance cost of the distribution center; g j Representing the unit management cost of the warehouse j to the goods; f (f) j Representing warehouse construction costs; z j Expressed as an integer variable from 0 to 1; l (L) jk Indicating whether the distribution line is selected; l represents a sufficiently large number.
The site selection model constructed in the embodiment is a 0-1 integer nonlinear programming model, and the right side of the equation respectively represents transportation cost, transportation vehicle refrigeration energy consumption, food goods loss cost, heat insulation ice bag refrigeration cost, distribution center warehouse management cost, distribution center construction cost and warehouse refrigeration cost. After the site selection model is constructed, programming solution is carried out on the site selection model by using simulation software, and a global optimal solution is obtained, wherein the optimal solution is the site selection result of the distribution center. Preferably, in this embodiment, the site selection model is solved by using Lingo software (the Lingo software may be used to solve nonlinear programming, and the execution speed is very fast, which is the best choice for solving the optimization model). For example, 7 alternative logistics distribution center addresses are provided, 3 suppliers supply products for the logistics distribution center addresses, 40 customers need products (namely, the demand points are 40), 3 alternative points need to be selected to establish the logistics distribution center, and related parameters are set as follows:
transportation stage unit transportation cost h=0.3; delivery stage unit transport cost h' =0.5; the vehicle refrigeration energy consumption cost per unit time in the transportation stage is w=39.2; fixed vehicle speed v=60 from the supplier to the distribution center; the fixed vehicle speed v' from the distribution center to the demand point is=20; rated load a=200 of the large transport vehicle; the capacity b=10 of the fresh box in the delivery stage; the cost d=10 of the fresh-keeping ice bag; monovalent q=50 for fresh product; the spoilage rate coefficient θ=0.3; the total customer demand is 471, and specifically, the customer demand of each customer is randomly set. Substituting the parameters into the constructed site selection model, solving the example by using the Lingo software, and carrying out 17068 steps of iteration to obtain the site selection results of 1, 3 and 4 alternative points, wherein the minimum total logistics cost is 5137.6.
Further, in order to know the influence of each parameter in the model on the site selection of the cold chain logistics distribution center, verification analysis is performed on the parameters in the model. Specifically, in this embodiment, sensitivity analysis is performed on the spoilage rate coefficient, the customer demand, the transport vehicle-mounted cargo amount and the insulation time in the insulation box in the delivery stage in the site selection model by using simulation software, so as to obtain the influence of the spoilage rate coefficient, the customer demand, the transport vehicle-mounted cargo amount and the insulation time in the insulation box in the delivery stage on the site selection result. The specific analysis is as follows:
(1) Decay Rate coefficient θ analysis
Because of the different spoilage rates of different varieties, for example, frozen seafood spoils faster and vegetables and other agricultural products spoil slower. The spoilage rate coefficient theta is now taken to be different values to analyze the change in total cost of the stream as the spoilage rate coefficient theta changes. Thereby obtaining the influence of the spoilage rate coefficient on the site selection strategy of the fresh product distribution center. According to the assumptions herein, the spoilage rate coefficient θ can lead to loss of fresh product during transport. The spoilage rate coefficient θ has an important effect on the distribution center site of fresh product cold chain streams, as shown in table 1.
TABLE 1 influence of the spoilage Rate coefficient θ on the location of a distribution center
As is clear from table 1, the spoilage rate coefficient θ varies depending on the type of cargo and the transportation conditions, and the total cost of the site selection of the distribution center increases as the loss rate increases. When the spoilage rate coefficient θ is 0.15< θ <0.25, the distribution cost (removal of the loss) gradually increases. When the spoilage rate coefficient θ >0.25, the delivery cost (with the loss removed) begins to decrease, the shipping cost begins to rise, the average shipping distance per unit of product decreases, the average shipping distance per unit of product increases, the vendor-to-delivery center distance decreases, and the delivery center is addressed closer to the customer. And when the addressing schemes are the same (e.g., addressing results of 1, 4, 7), the cost of goods loss increases as the spoilage rate coefficient θ increases.
(2) Sensitivity analysis of customer demand
The customer demand is not a constant but exhibits fluctuations from month to month. The customer demands of each customer at different times are now set, the demands of each customer are summed to give the total customer demand of the distribution center, and then the change of the site selection position of the distribution center along with the change of the total customer demand of the distribution center is analyzed, as shown in table 2.
TABLE 2 influence of customer demand on distribution center site selection
As can be derived from table 2, as customer demand increases, the distribution center site will select alternative points closer to the customer.
(3) Sensitivity analysis of the quantity of goods transported on board
According to the solving result, the embodiment selects common refrigerated vehicles with different specifications and models on the market at present for comparison, and analyzes the influence of the refrigerated vehicles on the total cost of logistics. The relevant data and the solving result are shown in table 3 and table 4.
Table 3 refrigerator car data selection
TABLE 4 influence of on-board cargo quantity transported on total cost of logistics
As can be seen from table 4, when the total demand of customers is small, the small refrigerator car is suitable for transportation, and the total cost of logistics is low; when the total demand of customers is large, the large-scale refrigerated truck is suitable for transportation, and the total cost of logistics is low.
(4) Sensitivity analysis of incubation time t' in incubator during delivery phase
In this embodiment, it is assumed that the heat preservation time of the goods is limited by adopting the measures of carton packing and ice bag heat preservation in the goods delivery stage. In the process of delivering the goods, as the ice cubes in the paper boxes are gradually melted, the storage and transportation temperature is continuously increased, and after the ice cubes are completely melted, the goods begin to spoil. The common heat-insulating ice bags in the market are selected, wherein one heat-insulating ice bag has the cost of 0.5 yuan/ton, the capacity of 600ml, the heat-insulating ice bag can be repeatedly used for about 100 times, and the ice making cost is 300 yuan/ton. We set up to put different numbers of ice bags in the cartons, resulting in different holding times t', analyzing their impact on the overall cost of the logistics.
TABLE 5 influence of the holding time of the delivery stage on the total cost of the logistics
As can be seen from the data of table 5, the overall cost of the logistics is initially reduced as the number of ice packs placed therein is increased, but is increased as the cost of the ice packs and ice making is increased when the number of ice packs reaches a certain number.
Further, based on the above embodiment, the present invention further provides an address selection system of a cold chain logistics distribution center based on goods loss, as shown in fig. 2, the address selection system includes:
an alternative point selection module 210, configured to select a plurality of addresses in the target area as alternative points of the distribution center;
a transportation condition determining module 220 for determining transportation conditions from the suppliers to the distribution centers and from the distribution centers to the demand points;
the site selection model construction module 230 is configured to determine a cost of goods according to the transportation condition, input a total cost including the cost of goods into the mathematical model, and construct a site selection model on the condition that the total cost is minimum;
the address selection result output module 240 is configured to solve the address selection model by using simulation software, and output an address selection result of the distribution center;
and the verification analysis module 250 is used for carrying out verification analysis on the site selection model by using simulation software and analyzing the influence of each parameter in the site selection model on the site selection result of the distribution center.
The principle and effects between the functional modules in this embodiment may refer to the above method embodiments, and will not be further described herein.
In summary, the invention provides a method and a system for selecting a cold chain logistics distribution center based on goods loss, wherein the method comprises the following steps: selecting a plurality of addresses in a target area as alternative points of a distribution center; determining the transportation conditions from the suppliers to the distribution centers and from the distribution centers to the demand points; determining the cost of goods loss according to the transportation condition, inputting the total cost of logistics including the cost of goods loss into a mathematical model, and constructing an address selection model under the condition that the total cost of logistics is minimum; and solving the site selection model by using simulation software, and outputting the site selection result of the distribution center. The invention constructs an addressing model with the aim of minimizing the total logistics cost based on the transportation condition of goods and taking the goods loss cost into consideration, so that the addressing of the cold-chain logistics distribution center is more real and reasonable, the optimal address can be selected for the distribution center, and the cost of the whole logistics process is reduced.
It is to be understood that the invention is not limited in its application to the examples described above, but is capable of modification and variation in light of the above teachings by those skilled in the art, and that all such modifications and variations are intended to be included within the scope of the appended claims.
Claims (3)
1. A method for locating a cold chain logistics distribution center based on a cargo loss, the method comprising:
selecting a plurality of addresses in a target area as alternative points of a distribution center;
determining the transportation conditions from the suppliers to the distribution centers and from the distribution centers to the demand points;
the transportation conditions include: refrigeration energy consumption of the transport vehicle from the supplier to each distribution center and heat preservation time in the heat preservation box in the distribution stage;
determining the cost of goods loss according to the transportation condition, inputting the total cost of logistics including the cost of goods loss into a mathematical model, and constructing an address selection model on the condition that the total cost of logistics is lower than a preset value;
the site selection model is as follows:
wherein,
xij≥0 ,yjk≥0 ,i＝1 ,2 ,3 ...M；j＝1 ,2 ,3 ...N；k＝1 ,2 ,3 ...P (11)
ljk =0 or 1, zj=0 or 1, j=1..n (12);
formula (1) indicates that the weight of goods from supplier i to each distribution center is within its production capacity; formula (2) represents a capacity limitation of the distribution center; equation (3) represents the customer demand amount at which the supply amount of each distribution center satisfies the demand point k; formula (4) represents that the goods received by each distribution center are equal to the goods sent out; formula (5) represents ensuring that at least one distribution center is established; equation (6) indicates that the number of established distribution centers cannot exceed p; equation (7) shows that each customer is only supplied by one distribution center; formula (8) shows that the distribution center has certain corresponding distribution clients, and the condition that the logistics distribution center is selected and no clients exist; the formulas (9) and (10) represent the relationship between the transport capacity and the alternative point; the formulas (11) and (12) represent constraints on the values of the parameters; wherein Q represents the total cost of the material flow; m represents the number of suppliers; n represents the number of alternative distribution centers; p represents the number of demand points; x is x ij Representing the traffic of supplier i to distribution center j; y is jk Representation ofThe traffic of the delivery point j to the demand point k; h represents the unit transportation cost in the transportation stage; h' represents the unit transportation cost in the delivery stage; r is (r) ij Representing the distance from supplier i to delivery point j; s is(s) jk Representing the distance from the distribution center j to the demand point k; a is that i Representing the capacity of supplier i; o (o) j A delivery upper limit indicating the delivery center j; d (D) k Representing customer demand for demand point k; v denotes a fixed vehicle speed from the supplier to the distribution center; v' represents a fixed vehicle speed from the distribution center to the demand point; a represents the rated cargo capacity of the large transport vehicle; b represents the capacity of the preservation box in the delivery stage; d represents the cost of a fresh box; w represents the vehicle refrigeration energy consumption cost per unit time in the transportation stage; q fresh represents the unit price of fresh product; c represents the fixed maintenance cost of the distribution center; g j Representing the unit management cost of the warehouse j to the goods; f (f) j Representing warehouse construction costs; z j Expressed as an integer variable from 0 to 1; l (L) jk Indicating whether the distribution center is selected; l represents a sufficiently large number;
the cost of goods is required to consider the rate of goods spoilage; the rate of the goods spoilage is related to the insulation time in the incubator during the delivery phase; considering the spoilage rate coefficient in sections, accurately representing the spoilage condition of goods;
the total cost of the logistics includes: transportation cost, refrigeration energy consumption of transportation vehicle quantity, food and goods loss cost, heat preservation ice bag refrigeration cost, warehouse management cost of a distribution center, construction cost of the distribution center and warehouse refrigeration cost;
based on the transportation condition of goods and taking the goods loss cost into consideration, constructing an address selection model with the object of minimizing the total cost of logistics, so that the address selection of a cold chain logistics distribution center is more real and reasonable;
solving the site selection model by using simulation software, and outputting the site selection result of the distribution center;
verifying and analyzing the site selection model by using simulation software, and analyzing the influence of each parameter in the site selection model on the site selection result of the distribution center and the total cost of the logistics;
the step of verifying and analyzing the site selection model by using simulation software to analyze the influence of each parameter in the site selection model on the site selection result of the distribution center and the total logistics cost comprises the following steps:
and carrying out sensitivity analysis on the spoilage rate coefficient, the customer demand, the transportation vehicle-mounted goods quantity and the heat preservation time in the heat preservation box in the delivery stage in the site selection model by using simulation software to obtain the influence of the spoilage rate coefficient, the customer demand, the transportation vehicle-mounted goods quantity and the heat preservation time in the heat preservation box in the delivery stage on site selection results and logistics total cost.
2. The method for locating a cold chain logistics distribution center based on cargo damage of claim 1, wherein the locating model is a 0-1 integer nonlinear programming model.
3. A system for locating a cold chain logistics distribution center based on a loss of goods according to any one of the preceding claims 1-2, said system comprising:
the alternative point selection module is used for selecting a plurality of addresses in the target area as alternative points of the distribution center;
the transportation condition determining module is used for determining transportation conditions from the suppliers to the distribution centers and from the distribution centers to the demand points;
the transportation conditions include: refrigeration energy consumption of the transport vehicle from the supplier to each distribution center and heat preservation time in the heat preservation box in the distribution stage;
the site selection model construction module is used for determining the cargo loss cost according to the transportation condition, inputting the logistics total cost including the cargo loss cost into the mathematical model, and constructing the site selection model under the condition that the logistics total cost is minimum;
the site selection model is as follows:
wherein,
xij≥0 ,yjk≥0 ,i＝1 ,2 ,3 ...M； j＝1 ,2 ,3 ...N；k＝1 ,2 ,3 ...P (11)
ljk =0 or 1, zj=0 or 1, j=1..n (12);
formula (1) indicates that the weight of goods from supplier i to each distribution center is within its production capacity; formula (2) represents a capacity limitation of the distribution center; equation (3) represents the customer demand amount at which the supply amount of each distribution center satisfies the demand point k; formula (4) represents that the goods received by each distribution center are equal to the goods sent out; formula (5) represents ensuring that at least one distribution center is established; equation (6) indicates that the number of established distribution centers cannot exceed p; equation (7) shows that each customer is only supplied by one distribution center; formula (8) shows that the distribution center has certain corresponding distribution clients, and the condition that the logistics distribution center is selected and no clients exist; the formulas (9) and (10) represent the relationship between the transport capacity and the alternative point; the formulas (11) and (12) represent constraints on the values of the parameters; wherein Q represents the total cost of the material flow; m represents the number of suppliers; n represents the number of alternative distribution centers; p represents the number of demand points; x is x ij Representing the traffic of supplier i to distribution center j; y is jk Representing the traffic volume from the delivery point j to the demand point k; h represents the unit transportation cost in the transportation stage; h' represents the unit transportation cost in the delivery stage; r is (r) ij Representing the distance from supplier i to delivery point j; s is(s) jk Representing the distance from the distribution center j to the demand point k; a is that i Representing the capacity of supplier i; o (o) j A delivery upper limit indicating the delivery center j; d (D) k Representing customer demand for demand point k; v denotes a fixed vehicle speed from the supplier to the distribution center; v' represents a fixed vehicle speed from the distribution center to the demand point; a represents the rated cargo capacity of the large transport vehicle; b represents the capacity of the preservation box in the delivery stage; d represents the cost of a fresh box; w represents the vehicle refrigeration energy consumption cost per unit time in the transportation stage; q fresh represents the unit price of fresh product; c represents the fixed maintenance cost of the distribution center; g j Representing the unit management cost of the warehouse j to the goods; f (f) j Representing warehouse construction costs; z j Expressed as an integer variable from 0 to 1; l (L) jk Indicating whether the distribution center is selected; l represents oneA number large enough;
the cost of goods is required to consider the rate of goods spoilage; the rate of the goods spoilage is related to the insulation time in the incubator during the delivery phase; considering the spoilage rate coefficient in sections, accurately representing the spoilage condition of goods;
the total cost of the logistics includes: transportation cost, refrigeration energy consumption of transportation vehicle quantity, food and goods loss cost, heat preservation ice bag refrigeration cost, warehouse management cost of a distribution center, construction cost of the distribution center and warehouse refrigeration cost;
based on the transportation condition of goods and taking the goods loss cost into consideration, constructing an address selection model with the object of minimizing the total cost of logistics, so that the address selection of a cold chain logistics distribution center is more real and reasonable;
the address selection result output module is used for solving the address selection model by using simulation software and outputting an address selection result of the distribution center;
the verification analysis module is used for carrying out verification analysis on the site selection model by using simulation software and analyzing the influence of each parameter in the site selection model on the site selection result of the distribution center and the total cost of the logistics;
the step of verifying and analyzing the site selection model by using simulation software to analyze the influence of each parameter in the site selection model on the site selection result of the distribution center and the total logistics cost comprises the following steps:
and carrying out sensitivity analysis on the spoilage rate coefficient, the customer demand, the transportation vehicle-mounted goods quantity and the heat preservation time in the heat preservation box in the delivery stage in the site selection model by using simulation software to obtain the influence of the spoilage rate coefficient, the customer demand, the transportation vehicle-mounted goods quantity and the heat preservation time in the heat preservation box in the delivery stage on site selection results and logistics total cost.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811348120.5A CN109636002B (en) | 2018-11-13 | 2018-11-13 | Cold chain logistics distribution center site selection method and system based on goods loss |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811348120.5A CN109636002B (en) | 2018-11-13 | 2018-11-13 | Cold chain logistics distribution center site selection method and system based on goods loss |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109636002A CN109636002A (en) | 2019-04-16 |
| CN109636002B true CN109636002B (en) | 2023-11-14 |
Family
ID=66067975
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811348120.5A Active CN109636002B (en) | 2018-11-13 | 2018-11-13 | Cold chain logistics distribution center site selection method and system based on goods loss |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109636002B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110211655A (en) * | 2019-06-06 | 2019-09-06 | 苏州瑞派宁科技有限公司 | Allocator, the delivery management apparatus and system of short-half-life drug |
| CN112308266B (en) * | 2019-07-26 | 2023-11-03 | 北京京东振世信息技术有限公司 | Warehouse location method, warehouse location device, warehouse location equipment and readable storage medium |
| CN111598359B (en) * | 2020-06-04 | 2023-11-21 | 上海燕汐软件信息科技有限公司 | Logistics station site selection method and system |
| CN111985792B (en) * | 2020-07-30 | 2023-12-29 | 中国外运股份有限公司 | Cold chain transport vehicle load balancing order arranging method and device and electronic equipment |
| CN112766862A (en) * | 2021-02-04 | 2021-05-07 | 浙江科技学院 | Method for dividing and locating distribution area of petrochemical product supply chain |
| CN113159686B (en) * | 2021-04-27 | 2023-09-22 | 重庆邮电大学 | Cold chain distribution network reliability assessment method considering transportation loss and distribution cost |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105373909A (en) * | 2015-12-04 | 2016-03-02 | 江苏省现代企业信息化应用支撑软件工程技术研发中心 | Logistics dispensing center addressing method based on simulation software |
-
2018
- 2018-11-13 CN CN201811348120.5A patent/CN109636002B/en active Active
Non-Patent Citations (2)
| Title |
|---|
| How to Locate the Cold Chain Logistics Distribution Center Based on the Gray Comprehensive Evaluation;Yu Bai等;2010 International Conference on E-Product E-Service and E-Entertainment;1-4 * |
| 孟光.生鲜农产品冷链物流配送中心选址研究.《中国优秀硕士学位论文全文数据库经济与管理科学辑》.2017,J149-1252. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109636002A (en) | 2019-04-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109636002B (en) | Cold chain logistics distribution center site selection method and system based on goods loss | |
| Dekker et al. | Operations Research for green logistics–An overview of aspects, issues, contributions and challenges | |
| He et al. | Prediction modelling of cold chain logistics demand based on data mining algorithm | |
| Lütjen et al. | Quality driven distribution of intelligent containers in cold chain logistics networks | |
| Awad et al. | Vehicle routing in cold food supply chain logistics: a literature review | |
| Jaegler et al. | Carbon friendly supply chains: a simulation study of different scenarios | |
| CN113935680A (en) | Cold-chain logistics intelligent management method and system based on big data | |
| CN114169825A (en) | Cold chain transportation line planning method, device, equipment and storage medium | |
| Hsu et al. | A model for facilities planning for multi-temperature joint distribution system | |
| CN107194755A (en) | The semi-automatic Carpooling system of one kind visualization and its method | |
| Fan et al. | Refer logistics and cold chain transport: A systematic review and multi-actor system analysis of an un-explored domain | |
| CN116452097A (en) | Urban distribution path decision-making method considering consumable materials under cold chain logistics | |
| Pan et al. | Deterioration rate variation risk for sustainable cross-docking service operations | |
| Habibur Rahman et al. | Estimation of fuel consumption and selection of the most carbon-efficient route for cold-chain logistics | |
| Gao et al. | A network flow model of regional transportation of e-commerce and analysis on maturity change of fresh fruit | |
| Su et al. | Path optimization of fresh products logistics distribution under new retail mode | |
| Zanoni et al. | Environmental impacts of foods refrigeration | |
| CN106628693A (en) | Standardized cold box system for cold-chain transportation and cold-chain transportation method | |
| CN112033086A (en) | Cold chain box with temperature and humidity capable of being measured and adjusted and control method thereof | |
| Jedermann et al. | 15 Years of Intelligent Container Research | |
| Marchi et al. | Energy efficiency in cold supply chains of the food and beverage sector | |
| Fang et al. | Research on long-distance cold chain logistics route optimization considering transport vibration and refrigerant carbon emission | |
| Tanner et al. | Sea transportation of fruits and vegetables: An update | |
| Shui et al. | Integrated thermal insulation packing and vehicle routing for perishable products in community group purchase | |
| Salam et al. | Generating an efficient way of dispatching perishable product optimization through exact and metaheuristic algorithm comparison |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |