CN101526971A - Method for setting input parameters of general simulation system used in container terminal logistics operation - Google Patents
Method for setting input parameters of general simulation system used in container terminal logistics operation Download PDFInfo
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- CN101526971A CN101526971A CN200910048511A CN200910048511A CN101526971A CN 101526971 A CN101526971 A CN 101526971A CN 200910048511 A CN200910048511 A CN 200910048511A CN 200910048511 A CN200910048511 A CN 200910048511A CN 101526971 A CN101526971 A CN 101526971A
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Abstract
The invention discloses a method for setting input parameters of a general simulation system used in container terminal logistics operation. The method is based on generality abstract and random variable extraction, and parameters determined by the method comprise system setting and selection parameters, ship parameters, loading bridge parameters, parameters of a horizontal handling system serving the loading bridge, parameters of a stockyard stacking system at dock apron, container transportation and collection and distribution system parameters. The input parameters determine modeling and simulation generality of a container terminal logistics operation system.
Description
Technical field:
The present invention relates to a kind of modeling method of the terminal logistics operation general simulation system of casing, the particularly a kind of input parameter of terminal logistics operation general simulation system and establishing method of stochastic variable of casing.
Background technology:
Input parameter is the power of emulation experiment, and these input parameters have determined the versatility of container terminal logistics operation system modeling and simulation.Most important parts is the stochastic variable parameter in the parameter of setting.
The container terminal logistics operation analogue system is typical discrete event dynamic system.In discrete event dynamic system, the generation drive system state of a discrete event changes, and also can excite new discrete event in system according to the operation rule of system simultaneously, thereby forms the evolutionary process of system state.In this type systematic, what the system action process was played a decisive role is a collection of discrete event, rather than continuous variable.Therefore, the model of determining stochastic variable is crucial.
Container terminal logistics operation analogue system based on discrete event dynamic system exists a large amount of stochastic variables, causes system's randomness, complicacy and dynamic feature obvious.
Based on the characteristics of above-mentioned parameter, thereby prior art has influenced the versatility of container terminal logistics operation system modeling and simulation in the defective of the setting existence of parameter.
Summary of the invention:
The present invention is directed to the not high situation of versatility of above-mentioned existing container terminal logistics operation system modeling and simulation, and the establishing method of proposition container terminal logistics operation system versatility model and simulation system parameters makes input parameter become the power of general simulation system experiment.
In order to achieve the above object, the technical solution adopted in the present invention is as follows:
The establishing method of input parameters of general simulation system used in container terminal logistics operation, this method is based upon on the basis that the abstract and stochastic variable of general character extracts, the parameter that this method is determined comprise to the setting of system with select parameter, boats and ships related parameter, unloader parameter, get systematic parameter, case and inland transport systematic parameter for the horizontal handling system parameter of unloader service, stockyard, wharf apron heap.
Whether described default and the setting of selecting parameter comprise selections of process machinery system, berth division, berth quantity, emulation T.T., simulation step length, case and water front length;
The setting of described boats and ships parameter comprise boats and ships to ETA estimated time of arrival pattern spaced apart, to port ship type feature, to port ship type distribution pattern, to port ship loading and unloading rate distribution pattern, load probability onto ship, production line lower limit that the probability of unloading a ship, boats and ships are unloaded a ship probability and all ship types simultaneously; And preceding 7 parameters are stochastic variable.
The setting of described unloader parameter comprises unloader type, unloader total amount, unloader efficiency of loading and unloading distribution pattern, unloader serviceability rate, unloader dispensing mode, and wherein unloader efficiency of loading and unloading distribution pattern is a stochastic variable;
The setting of described horizontal handling system parameter comprises that every lines is equipped with mechanical number, horizontal mechanical serviceability rate, horizontal mechanical cycle of operation distribution pattern and horizontal mechanical dead time distribution pattern, and wherein horizontal mechanical cycle of operation distribution pattern and horizontal mechanical dead time distribution pattern are stochastic variable;
The setting that stockyard, described wharf apron heap is got systematic parameter comprises mechanical total amount, availability rate of machinery, mechanical efficiency distribution pattern, marshalling yard machinery quantity and stockyard, rear machinery quantity, and wherein the mechanical efficiency distribution pattern is a stochastic variable;
The setting of the described parameter system of falling the case comprises the time of falling the case, the ratio of falling the case, horizontal mechanical quantity, horizontal mechanical cycle of operation distribution pattern, horizontal mechanical dead time distribution pattern, the anterior-posterior stockyard of falling case machinery quantity, the back-preceding stockyard of falling case machinery quantity and stockyard mechanical efficiency distribution pattern, and wherein horizontal mechanical cycle of operation distribution pattern, horizontal mechanical dead time distribution pattern and stockyard mechanical efficiency distribution pattern are stochastic variable;
The setting of described inland transport systematic parameter comprises access mouth transporting something containerized efficient distribution pattern and goes out road junction transport efficient distribution pattern, and all is stochastic variable.
Described variable immediately carries out match by following steps:
(1) at first is distribution identification, utilizes frequency to distribute and set up histogram stochastic variable;
(2) carry out the hypothesis of distribution pattern again;
(3) degree of fitting of this distribution pattern is tested, if pass through, then determine this at random discrete event meet this distribution, if do not pass through, then the use experience distribution form is imported as parameter.
The present invention who obtains according to technique scheme makes input parameter become the power of general simulation system experiment.The major parameter of setting is based upon on the basis that general character is abstract and stochastic variable is extracted, and these input parameters have determined the versatility of container terminal logistics operation system modeling and simulation.
Description of drawings:
Further specify the present invention below in conjunction with the drawings and specific embodiments.
Fig. 1 is the graph of a relation of parameter among the present invention.
Embodiment:
For technological means, creation characteristic that the present invention is realized, reach purpose and effect is easy to understand, below in conjunction with concrete diagram, further set forth the present invention.
Input parameter is the power of emulation experiment.On the basis of abstract in general character in stochastic variable, contrast versatility characteristics of demand has been set seven class parameters.That is: the setting of system has related parameter, unloader that related parameter is arranged, gets systematic parameter, case and inland transport systematic parameter for the horizontal handling system parameter of unloader service, stockyard, wharf apron heap with selecting parameter, boats and ships.(as shown in Figure 1) specific as follows:
Whether default and the setting of selecting parameter comprise selections of process machinery system, berth division, berth quantity, emulation T.T., simulation step length, case and water front length;
The setting of boats and ships parameter comprise boats and ships to ETA estimated time of arrival pattern spaced apart, to port ship type feature, to port ship type distribution pattern, to port ship loading and unloading rate distribution pattern, load probability onto ship, production line lower limit that the probability of unloading a ship, boats and ships are unloaded a ship probability and all ship types simultaneously; And preceding 7 parameters are stochastic variable.
The setting of unloader parameter comprises unloader type, unloader total amount, unloader efficiency of loading and unloading distribution pattern, unloader serviceability rate, unloader dispensing mode, and wherein unloader efficiency of loading and unloading distribution pattern is a stochastic variable;
The setting of horizontal handling system parameter comprises that every lines is equipped with mechanical number, horizontal mechanical serviceability rate, horizontal mechanical cycle of operation distribution pattern and horizontal mechanical dead time distribution pattern, and wherein horizontal mechanical cycle of operation distribution pattern and horizontal mechanical dead time distribution pattern are stochastic variable;
The setting that stockyard, wharf apron heap is got systematic parameter comprises mechanical total amount, availability rate of machinery, mechanical efficiency distribution pattern, marshalling yard machinery quantity and stockyard, rear machinery quantity, and wherein the mechanical efficiency distribution pattern is a stochastic variable;
The setting of the parameter system of falling the case comprises the time of falling the case, the ratio of falling the case, horizontal mechanical quantity, horizontal mechanical cycle of operation distribution pattern, horizontal mechanical dead time distribution pattern, the A of falling case stockyard machinery quantity, the B of falling case stockyard machinery quantity (the A here, B does not possess concrete implication, it is a code name, showing has two case districts need fall case, pour another case district into from a case district, A and B may be any two the case districts in the stockyard), and stockyard mechanical efficiency distribution pattern, wherein horizontal mechanical cycle of operation distribution pattern, horizontal mechanical dead time distribution pattern and stockyard mechanical efficiency distribution pattern are stochastic variable;
The setting of inland transport systematic parameter comprises access mouth transporting something containerized efficient distribution pattern and goes out road junction transport efficient distribution pattern, and all is stochastic variable.
Setting according to above-mentioned parameter can make general modeling and emulation reach following requirement aspect the resource distribution:
Be applicable to the emulation of any a plurality of container berths;
How using the berth of harbour, is that to adopt the berth to count static state constant, still dynamically determines berth and quantity thereof according to water front and ship type;
Water front is the harbour of straight line/broken line
Plant the harbour production that the ship type triggers to the port arbitrarily;
The ratio of determining to reach various types of each link machinery quantity;
Whether the casing working that falls is favourable.
The major parameter of the present invention's design is made up of stochastic variable and nonrandom variable parameter two parts.
In the discrete analogue system,, in simulation process, need repeatedly to handle a large amount of enchancement factors because the real system that is reflected all comprises the reciprocation and the influence of multiple enchancement factor.No matter it is the various occurrences of random events moment, or the arrival stream that produces interim entity and the residence time of interim entity in analogue system etc., it all is the stochastic variable that different probability distributes, each simulation run all will be carried out random sampling from these probability distribution, so that obtain the actual parameter of current simulation run.
The stochastic variable that the present invention relates to mainly is divided into two classes: the stochastic variable stochastic variable relevant with boats and ships that mechanical efficiency is relevant.
The relevant stochastic variable of mechanical efficiency wherein
The stochastic variable that mechanical efficiency is relevant is the abstract acquisition of general character according to general simulation system.Comprise: the carrying of container bridge efficient, level working time and dead time, stockyard mechanical efficiency, access mouth transporting something containerized efficient, go out in road junction transport efficient, the process of falling the case horizontal handling machinery carrying cycle etc.
1, container bridge efficient is meant the per hour container amount of loading or unloading of container bridge, and unit is TEU/ hour.
2, the level carrying cycle is meant the carrying cycle of horizontal handling machinery between wharf apron and stockyard between wharf apron and the stockyard, comprise vehicle operating and dead time, specifically comprise four time sums: the horizontal handling machinery cycle of operation, horizontal handling machinery are waited for dead time, the dead time when horizontal handling machinery is waited for lift van in the stockyard, the improper dead time of horizontal handling machinery when operation of loading and unloading ship time between wharf apron and the stockyard in the wharf apron.These four times all are stochastic variables.
3, the stockyard mechanical efficiency comprises tire transfer gantry efficient and rail gantry crane efficient;
Tire transfer gantry efficient is meant the container amount that the tire transfer gantry is per hour handled, and unit is TEU/ hour.
Rail gantry crane efficient is meant the container amount that rail gantry crane is per hour handled, and unit is TEU/ hour.
4, transporting something containerized enters the container efficient at road junction
The container efficient that transporting something containerized enters the road junction is meant the container amount that is per hour entered by the road junction in the road junction link, and unit is TEU/ hour.
5, the transport container efficient that goes out the road junction is meant the container amount that is per hour gone out the stockyard in the road junction link by the road junction, and unit is TEU/ hour.
6, falling in the casing working horizontal handling machinery carrying cycle is made up of three part-times: improper dead time of horizontal handling machinery in horizontal handling machinery wait lift van dead time, the process of falling the case in the horizontal handling machinery cycle of operation, the process of falling the case in the process of falling the case.
7, fall that the stockyard mechanical efficiency comprises tire transfer gantry efficient and rail gantry crane efficient in the casing working;
Tire transfer gantry efficient is meant the container amount that the tire transfer gantry is per hour handled, and unit is TEU/ hour.
Rail gantry crane efficient is meant the container amount that rail gantry crane is per hour handled, and unit is TEU/ hour.
The stochastic variable that boats and ships are relevant
1, is meant boats and ships vanning number or unload the ratio that the case number accounts for the maximum container capacity of boats and ships behind the port to port ship loading and unloading rate, represents with number percent.
2, to port ship type feature: the boats and ships that arrive the harbour are at random, are stochastic variables to port ship type feature therefore, and its feature is made up of ship type classification, maximum container capacity, captain, spacing requirement etc.
3, distribute to port ship type: by the various ratios of being formed to port ship type feature to the port Ship Types are stochastic variables, represent with ship type classification and number percent thereof.
4, to port ship loading and unloading rate: during to the port ship loading and unloading, be not to exceed with maximum container capacity to load and unload, and a certain proportion of container requirement loading and unloading are just arranged, this ratio is exactly to port ship loading and unloading rate.To port ship loading and unloading rate is a stochastic variable, and number percent is represented.
5, load probability onto ship, unload a ship probability and boats and ships load and unload probability simultaneously: behind the ship berthing, may load onto ship, may unload a ship, also may load and unload ship simultaneously.
The ratio of shipment is called the shipment probability, represents with number percent;
The ratio of unloading a ship is called the probability of unloading a ship, and represents with number percent;
The probability that loads and unloads ship simultaneously is called boats and ships and loads and unloads probability simultaneously, represents with number percent.Therefore, shipment probability, unload a ship probability and boats and ships load and unload the probability sum simultaneously and equal 1.
The data acquisition scope of above-mentioned stochastic variable mainly comprises: boats and ships to ETA estimated time of arrival at interval; Boats and ships are to port operating type distribution pattern; Unloader efficient; Tire transfer gantry efficient; Access mouth transporting something containerized efficient; Go out road junction transport efficient; Level carrying working time and dead time etc.
Wherein image data is as follows:
Every case lay time of unloader: after leaving truck from the suspender of unloader, the concluding time is for before the suspender through one-period circulation back unloader leaves truck.
The level carrying is cycle length: wait for the unloader lift van time in the wharf apron, carrying working time, wait for the transfer gantry lift van time in the stockyard, travel in the middle of improper dead time sum.
Stockyard machinery is stored up the time, and it comprises the heap case time and gets the case time.
Pile case: till beginning to lift by crane before the next container from lifting container on the truck to truck;
Get case: container is placed on truck begins till next container is placed on before the truck.Wherein, if mould turnover is arranged, should write down the mould turnover number of times one by one.
The distribution pattern supposition of system's stochastic variable has multiple: inductive statistics amount method, histogram method, probability graph method, experience distribution etc.
At above stochastic variable sorting technique, the present invention has two kinds to the distribution pattern supposition method of stochastic variable:
Distribution pattern supposition method to " stochastic variable that mechanical efficiency is relevant ": at first adopt histogram method that stochastic variable is carried out match; If a kind of in the distribution of stochastic variable index of coincidence, normal distribution, binomial distribution, the Poisson distribution then is defined as it this distribution pattern, and calculate relevant parameters; If do not meet, then it is defined as the experience distribution pattern.
Distribution pattern supposition method to " stochastic variable that boats and ships are relevant " adopts the experience location mode.
2, the fitting algorithm of system's stochastic variable
Histogram be according to the sample obtained (X1, X2 ..., the fundamental figure of the density function that distribution Xn) is drawn carries out the supposition of distribution pattern; Experience distributes and to be meant and merely to utilize observation data to generate probabilistic model, no longer chooses a known theoretical distribution and designs distribution parameter and go match observation data [3].
The histogram-fitting of the discrete event at random algorithm that this paper proposes comprises: at first be the identification that distributes, utilize frequency to distribute and set up histogram, carry out distributional assumption again; Be the degree of fitting check of this distribution then, if pass through, then determine this at random discrete event meet this distribution, if do not pass through, then the use experience distribution form is imported as parameter.
Concrete match step is as follows, and it is the fitting algorithm of normal distribution:
1. i raw data X is provided, and wherein i satisfies i 〉=50, and deletes some obviously irrational too big and too little number.
2. analogue system is found out from sample data
With
3. establish analogue system and get between emulation zone and to be [a, b], wherein a and b satisfy
The value suggestion of wherein interval group number m is
4. determine that the user determines interval size, but the native system adopted value is (b-a)/m.
5. establish analogue system statistical sample data and fall into each sub-range (t
i, t
I+1) on number (frequency) be f
i, promptly drop on the 1st interval (t
1, t
2) on f is arranged
1, drop on m interval (t
m, t
M+1) on f is arranged
m
6. analogue system is drawn frequency histogram automatically.Analogue system is at (t
i, t
I+1) on make rectangle, the height h
i=f
i, i=1 wherein, 2 ..., m.
7. the user observes histogram, selects distribution pattern
For example scheme vivid normal distribution, calculate its parameter μ and σ estimated value, then initial option N (μ, σ
2) be the probability distribution of X.
8. theoretical probability value on the analogue system computation interval: calculate the probability on each minizone for convenience, at first with x~N (μ, σ
2) standardization,
Order
And with the value of Y expand for (∞ ,+∞).
Ask
The standardized normal distribution table that analogue system is looked into system to be provided gets Φ (Y
m)
(9) analogue system is carried out x
2Check:
Calculate
Analogue system is made hypothesis check, H
0: x~N (μ, σ
2), "as if" statistics amount x
0 2At H
0Obey x during establishment
2(m-r-1), look into x
2Show x
α 2(m-r-1), α is the level of signifiance.If
Then accept hypothesis H
0Otherwise,, then do not accept to suppose H
0, analogue system returned for the 7th step asks the user to reselect distribution, and system is match once more.
More than show and described ultimate principle of the present invention and principal character and advantage of the present invention.The technician of the industry should understand; the present invention is not restricted to the described embodiments; that describes in the foregoing description and the instructions just illustrates principle of the present invention; without departing from the spirit and scope of the present invention; the present invention also has various changes and modifications, and these changes and improvements all fall in the claimed scope of the invention.The claimed scope of the present invention is defined by appending claims and equivalent thereof.
Claims (9)
1, the establishing method of input parameters of general simulation system used in container terminal logistics operation, this method is based upon on the basis that general character is abstract and stochastic variable is extracted, it is characterized in that, the parameter that this method is determined comprise to the setting of system with select parameter, boats and ships related parameter, unloader parameter, get systematic parameter, case and inland transport systematic parameter for the horizontal handling system parameter of unloader service, stockyard, wharf apron heap.
2, the establishing method of input parameters of general simulation system used in container terminal logistics operation according to claim 1, it is characterized in that whether described default and the setting of selecting parameter comprise selections of process machinery system, berth division, berth quantity, emulation T.T., simulation step length, case and water front length;
3, the establishing method of input parameters of general simulation system used in container terminal logistics operation according to claim 1, it is characterized in that, the setting of described boats and ships parameter comprise boats and ships to ETA estimated time of arrival pattern spaced apart, to port ship type feature, to port ship type distribution pattern, to port ship loading and unloading rate distribution pattern, load probability onto ship, production line lower limit that the probability of unloading a ship, boats and ships are unloaded a ship probability and all ship types simultaneously; And preceding 7 parameters are stochastic variable.
4, the establishing method of input parameters of general simulation system used in container terminal logistics operation according to claim 1, it is characterized in that, the setting of described unloader parameter comprises unloader type, unloader total amount, unloader efficiency of loading and unloading distribution pattern, unloader serviceability rate, unloader dispensing mode, and wherein unloader efficiency of loading and unloading distribution pattern is a stochastic variable;
5, the establishing method of input parameters of general simulation system used in container terminal logistics operation according to claim 1, it is characterized in that, the setting of described horizontal handling system parameter comprises that every lines is equipped with mechanical number, horizontal mechanical serviceability rate, horizontal mechanical cycle of operation distribution pattern and horizontal mechanical dead time distribution pattern, and wherein horizontal mechanical cycle of operation distribution pattern and horizontal mechanical dead time distribution pattern are stochastic variable;
6, the establishing method of input parameters of general simulation system used in container terminal logistics operation according to claim 1, it is characterized in that, the setting that stockyard, described wharf apron heap is got systematic parameter comprises mechanical total amount, availability rate of machinery, mechanical efficiency distribution pattern, marshalling yard machinery quantity and stockyard, rear machinery quantity, and wherein the mechanical efficiency distribution pattern is a stochastic variable;
7, the establishing method of input parameters of general simulation system used in container terminal logistics operation according to claim 1, it is characterized in that, the setting of the described parameter system of falling the case comprises the time of falling the case, the ratio of falling the case, horizontal mechanical quantity, horizontal mechanical cycle of operation distribution pattern, horizontal mechanical dead time distribution pattern, the anterior-posterior stockyard of falling case machinery quantity, back-preceding the stockyard of falling case machinery quantity, and stockyard mechanical efficiency distribution pattern, wherein horizontal mechanical cycle of operation distribution pattern, horizontal mechanical dead time distribution pattern and stockyard mechanical efficiency distribution pattern are stochastic variable;
8, the establishing method of input parameters of general simulation system used in container terminal logistics operation according to claim 1, it is characterized in that, the setting of described inland transport systematic parameter comprises access mouth transporting something containerized efficient distribution pattern and goes out road junction transport efficient distribution pattern, and all is stochastic variable.
According to the establishing method of each described input parameters of general simulation system used in container terminal logistics operation in the claim 2 to 8, it is characterized in that 9, described variable immediately carries out match by following steps:
(1) at first is distribution identification, utilizes frequency to distribute and set up histogram stochastic variable;
(2) carry out the hypothesis of distribution pattern again;
(3) degree of fitting of this distribution pattern is tested, if pass through, then determine this at random discrete event meet this distribution, if do not pass through, then the use experience distribution form is imported as parameter.
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105205545A (en) * | 2015-02-13 | 2015-12-30 | 红塔烟草(集团)有限责任公司 | Method for optimizing logistics system by applying simulation experiment |
CN105719008A (en) * | 2015-05-22 | 2016-06-29 | 北京小度信息科技有限公司 | Method and device for performing optimization on delivery system |
-
2009
- 2009-03-30 CN CN200910048511A patent/CN101526971A/en active Pending
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105205545A (en) * | 2015-02-13 | 2015-12-30 | 红塔烟草(集团)有限责任公司 | Method for optimizing logistics system by applying simulation experiment |
CN105719008A (en) * | 2015-05-22 | 2016-06-29 | 北京小度信息科技有限公司 | Method and device for performing optimization on delivery system |
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Application publication date: 20090909 |