CN110705815A - Shop scheduling system and method - Google Patents

Shop scheduling system and method Download PDF

Info

Publication number
CN110705815A
CN110705815A CN201910740157.0A CN201910740157A CN110705815A CN 110705815 A CN110705815 A CN 110705815A CN 201910740157 A CN201910740157 A CN 201910740157A CN 110705815 A CN110705815 A CN 110705815A
Authority
CN
China
Prior art keywords
time
staff
employee
duty
scheduling
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.)
Pending
Application number
CN201910740157.0A
Other languages
Chinese (zh)
Inventor
黄世志
庞惠东
叶心雨
洪涛
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Ruixing Coffee Information Technology Xiamen Co Ltd
Original Assignee
Ruixing Coffee Information Technology Xiamen Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Ruixing Coffee Information Technology Xiamen Co Ltd filed Critical Ruixing Coffee Information Technology Xiamen Co Ltd
Priority to CN201910740157.0A priority Critical patent/CN110705815A/en
Publication of CN110705815A publication Critical patent/CN110705815A/en
Pending legal-status Critical Current

Links

Images

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
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06315—Needs-based resource requirements planning or analysis
    • 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
    • G06Q10/10—Office automation; Time management
    • G06Q10/109—Time management, e.g. calendars, reminders, meetings or time accounting
    • G06Q10/1093—Calendar-based scheduling for persons or groups
    • G06Q10/1097—Task assignment

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • Tourism & Hospitality (AREA)
  • Marketing (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Game Theory and Decision Science (AREA)
  • Development Economics (AREA)
  • Educational Administration (AREA)
  • Data Mining & Analysis (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The application discloses store scheduling system and method, wherein the store scheduling system comprises: the receiving module is used for responding to the received scheduling instruction and receiving the staff demand of each time period of the store; the acquisition module is used for acquiring prestored staff to be scheduled and the working time period of the staff; the constraint module is used for determining staff to be scheduled meeting preset constraint conditions; the scheduling determining module is used for determining the optimal scheduling combination of the staff, which meets the staff demand and minimizes the labor cost, according to the determined staff to be scheduled and the labor cost objective function; and the output module is used for outputting the scheduling data according to the determined optimal staff scheduling combination. The system and the method of the invention improve the scheduling speed and efficiency, and can schedule the personnel resources of enterprises most cost-effectively and realize the optimal allocation of resources.

Description

Shop scheduling system and method
Technical Field
The present application relates to the field of data processing systems or methods specifically adapted for administrative, business, financial, management, supervisory or forecasting purposes, and more particularly to store scheduling systems and methods.
Background
The invention related to the scheduling is mostly applied to the fields of hospital human resource management, bus system planning scheduling, airline scheduling and the like, and is a research invention for scheduling for cafes, restaurants and other stores. In addition, at present, enterprise units such as restaurants, KTVs, quick restaurants and the like employ some part-time employees, due to the category difference of the part-time employees and the part-time employees, and in order to reduce the management difficulty, considering the productivity constraint, enterprises tend to preferentially select the part-time employees and then use the part-time employees to supplement the extra personnel demands. The traditional shift arrangement is usually carried out manually, and the person in charge of shift arrangement determines the working time of each employee according to the number of the employees required in each time period. Due to the fact that a plurality of limiting factors need to be considered in the scheduling process, manual scheduling consumes more time, the scheduling quality cannot be guaranteed, and the scheduling efficiency is low.
Under the condition that the employees comprise full-time and part-time employee configurations, the employees have priority constraints, the working requirements of the employees meet a plurality of limiting conditions such as continuity constraints, the scheduling difficulty is improved to a new order, the scheduling time is long, and higher requirements are provided for a scheduling system.
Disclosure of Invention
The objective of the present application is to provide a system and method for scheduling in an store, in particular in a restaurant industry store, which can improve the scheduling speed and efficiency, and organize, plan, schedule and allocate the personnel resources of the enterprise most cost-effectively.
To solve the above technical problem, according to a first aspect of the present invention, there is provided a store shift system, comprising:
the receiving module is used for responding to the received scheduling instruction and receiving the staff demand of each time period of the store;
the acquisition module is used for acquiring prestored staff to be scheduled and the working time period of the staff;
the constraint module is used for determining staff to be scheduled meeting preset constraint conditions;
the scheduling determining module is used for determining the optimal scheduling combination of the staff, which meets the staff demand and minimizes the labor cost, according to the determined staff to be scheduled and the labor cost objective function;
and the output module is used for outputting the scheduling data according to the determined optimal staff scheduling combination.
As a refinement of the first aspect of the invention, the predetermined constraint includes one or more of: productivity constraints, people number constraints, and man-hour constraints.
As another improvement of the first aspect of the present invention, the labor cost is the sum of the working hours of the full-time employees, the working hours of the part-time employees, the working number of the full-time employees, and the working number of the part-time employees, and the optimal scheduling combination of the employees is determined by the scheduling determination module according to the following objective function:
Figure BDA0002163653500000021
wherein: n is the number of full-time members of the store, M is the number of part-time members of the store, S is the total number of scheduling periods of one day, K is the number of days of the week, K is the kth day, i is the ith staff, j is the jth period, Pr is the number of daysiRepresenting the scheduling weight of the ith full-time employee; ff (a)kijIndicating whether the full-time employee i is on duty in the jth time interval on the kth day, wherein the duty is 1, and the duty is 0 if the full-time employee i is not on duty; pp (polypropylene)kijIndicating whether the part-time employee i on the kth day is on duty in the jth time period, wherein the duty is 1, and the duty is 0 if the part-time employee i is not on duty; ftkiIndicating whether the full-time employee i on the kth day is on duty or not, wherein the on duty is 1, and the off duty is 0; pt iskiIndicating whether the day i of the part-time employee on the kth day is on duty, wherein the duty is 1, and the duty is 0 if the day i is not on duty; the coefficient θ is a weighting coefficient of the part-time employee.
As a further refinement of the first aspect of the invention, the constraint module comprises a productivity constraint sub-module that determines whether the staff to be scheduled at each time interval has a human effort greater than or equal to the staff demand at the corresponding time interval.
As a further improvement of the first aspect of the present invention, the constraint module comprises a people number constraint submodule, and the people number constraint submodule determines whether the same time interval during the working hours meets the requirement of the number of people on duty and whether the same time interval during the working hours meets the requirement of the number of people of full-time employees.
As a further refinement of the first aspect of the invention, the constraint module includes a man-hour constraint submodule that determines whether one or more of the following conditions are satisfied:
1) the working hours of the full-time staff every day are [ f ]low，fhigh]To (c) to (d);
2) the working hours of the part-time staff every day are [ p ]low，phigh]To (c) to (d);
3) the working hours of the full-time staff are in every weeklow-week，fhigh-week]To (c) to (d);
4) the working days of the full-time staff per week are less than or equal to the preset days;
5) providing the staff working in the dining time period with the dining time of at least 1 time period;
6) the full-time staff and the part-time staff meet the working continuity constraint condition;
wherein f ishighRepresents the longest working time of the full-time employee in the day, flowRepresents the shortest working time of the full-time staff in the day, phighRepresents the longest working time of the part-time employee in the day, plowIndicating the shortest working time of the part-time employee in the day, flow-weekRepresents the shortest working time of the full-time employee in one week, fhigh-weekRepresenting the longest working time of a full-time employee in a week.
As a further refinement of the first aspect of the present invention, the man-hour constraint sub-module determines whether the full-time employee or the part-time employee meets the requirements for scheduling meal times by the following formula:
Figure BDA0002163653500000031
for a full-time employee,
Figure BDA0002163653500000033
for part timeThe number of the employees is increased, and the employees,
where B is a set of meal periods, j ∈ B indicates that j belongs to a meal period, BkijIndicating whether the employee i schedules a meal in the jth time period on the kth day, wherein the scheduled meal is 1, and the non-scheduled meal is 0; skijRepresenting the planned working hour arrangement of the employee i in the jth time period on the kth day, wherein the planned working hour is 1, and otherwise, the planned working hour is 0; len (b) indicates the length of the meal period.
As a further improvement of the first aspect of the present invention, the man-hour constraint sub-module determines whether the full-time employee or the part-time employee satisfies the on-duty continuity constraint by the following formula:
Figure BDA0002163653500000041
skij-ski(j-1)+ukij-vkij＝0，j≥2
ukij+vkij≤1，j≥2
for a full-time employee,for the part-time employees, the employee is,
Figure BDA0002163653500000043
wherein s iski1Whether the ith employee is on duty in the 1 st period for the kth day, ukijAnd vkijAre all intermediate variables introduced.
As another improvement of the first aspect of the present invention, the system further comprises a checking module for checking whether the optimal shift combination of the employee meets the requirements after outputting the shift data.
According to a second aspect of the present invention, there is provided a store shift scheduling method, comprising:
receiving staff demand of each time period of the store in response to the received scheduling instruction;
acquiring pre-stored staff to be scheduled and the working time period thereof;
determining staff to be scheduled which meet preset constraint conditions;
determining an optimal scheduling combination of the staff, which meets the staff demand and minimizes the labor cost, according to the determined staff to be scheduled and the labor cost objective function;
and outputting scheduling data according to the determined optimal scheduling combination of the employees.
The system or the method is executed on the computer, and by receiving the staff demand of the store, determining the staff to be scheduled meeting the preset constraint condition from the staff to be scheduled, and then determining the staff optimal scheduling combination meeting the staff demand and minimizing the labor cost according to the determined staff to be scheduled, the complex problem of manual scheduling is solved, the scheduling speed and efficiency are improved, the staff resources of an enterprise can be scheduled most cost-effectively, and the resource optimal configuration is realized. In addition, under the condition of considering constraint conditions such as continuous work of employees and the like, due to the increased scheduling complexity, the calculated amount required by scheduling is greatly increased, and the calculated amount of a scheduling system is greatly reduced through a newly designed objective function and a newly designed model, so that the scheduling efficiency is further improved.
Drawings
Fig. 1 is a block diagram showing the configuration of an embodiment of a store shift arrangement system according to the present invention.
Fig. 2 is a flowchart of an embodiment of a store scheduling method according to the present invention.
For the sake of clarity, the figures are schematic and simplified drawings, which only show details which are necessary for understanding the invention and other details are omitted.
Detailed Description
Embodiments and examples of the present invention will be described in detail below with reference to the accompanying drawings.
The scope of applicability of the present invention will become apparent from the detailed description given hereinafter. It should be understood, however, that the detailed description and the specific examples, while indicating preferred embodiments of the invention, are given by way of illustration only.
Fig. 1 shows an embodiment of a store scheduling system according to the invention, which is particularly suitable for scheduling of catering industry stores including full-time and part-time employees, such as coffee stores of a large coffee chain. The scheduling system shown in fig. 1 includes a receiving module 101, an obtaining module 102, a constraint module 103, a scheduling determination module 104, and an output module 105.
The receiving module 101 is configured to receive staff demand of each time period of the store in response to receiving the shift scheduling instruction. In a preferred embodiment, the staff demand in each time period is provided by an store to be scheduled, the time period is divided into one time period of 30 minutes, and the staff demand in all the time periods of a week is provided according to the business hours of the store. The time period may also be divided by other lengths as desired, such as 20 minutes or one hour.
The obtaining module 102 is used for obtaining pre-stored names or numbers of employees to be scheduled and working time period conditions of the employees.
The constraint module 103 is used for determining staff to be scheduled meeting preset constraint conditions. In an embodiment, the predetermined constraint includes one or more of: productivity constraints, people number constraints, and man-hour constraints. The preset constraint condition may also include other constraint conditions according to actual needs.
The productivity constraint condition means that the scheduling manpower in each period of the week should be greater than or equal to the predicted demand manpower, and is expressed as:
Figure BDA0002163653500000061
ffkijand ppkijRespectively indicating whether the employee i is on duty in the jth time interval on the kth day, wherein the working time intervals are effective working time intervals with the dining time interval deducted, and dkjThe staff demand in the jth period of the kth day is represented, and the actual staff demand, namely the staff deducting the rest in the dining period, is represented here. According to requirements, the number of staff scheduled in the same time period should be greater than or equal to the minimum staff requirement required in the time period.
The constraint conditions of the number of people comprise: at least alpha staff are on duty in the same time interval during working hours, and at least beta full-time staff are on duty in the same time interval during working hours, which are expressed as:
Figure BDA0002163653500000063
wherein fs iskijIndicating whether the full-time employee i is on duty in the jth time interval on the kth day, wherein the duty is 1, and the duty is 0 if the full-time employee i is not on duty; ps iskijIndicating whether the part-time employee i on the kth day is on duty in the jth time period, wherein the on duty is 1, and the off duty is 0; fs iskijAnd pskijIndicates whether the employee is scheduled for work, i.e., without deducting meal time. The values of alpha and beta are preset by stores to be scheduled according to actual needs. For example, when α is 2 and β is 1, it means that at least 2 people are on duty during the same period of time and at least 1 full-time employee is on duty during the same period of time.
The man-hour constraints include one or more of the following conditions:
1) the working hours of the full-time staff every day are [ f ]low，fhigh]To (c) to (d);
2) the working hours of the part-time staff every day are [ p ]low，phigh]To (c) to (d);
3) the working hours of the full-time staff are in every weeklow-week，fhigh-week]To (c) to (d);
4) the working days of the full-time staff per week are less than or equal to 6 days;
5) the method comprises the steps of providing 1 time period of dining time for staff working at a dining time period;
6) the full-time staff and the part-time staff meet the working continuity constraint condition.
Wherein f ishighRepresents the longest working time of the full-time employee in the day, flowRepresents the shortest working time of the full-time staff in the day, phighRepresents the longest working time of the part-time employee in the day, plowIndicating the shortest working time of the part-time employee in the day, flow-weekIndicating that the full-time employee is shortest in a weekLength of operation, fhigh-weekRepresenting the longest working time of a full-time employee in a week. The working hours (working hours) are all hours, and since it has been assumed that the staff requirement of each time interval is provided in 30 minutes as one time interval, in the following modeling and algorithm design, the working hours are all converted into corresponding time intervals for calculation, that is, 1 hour is converted into 2 time intervals.
The daily working hours of full-time employees are represented as:
Figure BDA0002163653500000071
Figure BDA0002163653500000072
wherein f ishighAnd flowThe unit is hour, the unit is multiplied by 2 to be converted into a time interval, and the expression indicates that for the k day, the full-time employee i is not on duty or is on duty and meets the working duration constraint.
In one embodiment, fhigh＝11，flow6 means that the full-time staff needs to work for 6-11 hours every day, that is, if a certain full-time staff works on the day, the staff needs to work for 6-11 hours, or does not work. Note that the unit here is an hour, and if brought into the model, both need to be multiplied by 2, turning to the period for calculation.
The working hours of the part-time employees on duty every day are expressed as:
wherein p ishighAnd plowThe unit is hour, the unit is multiplied by 2 to be converted into a time interval, and the expression indicates that on the k day, the part-time employee i is not on duty or on duty and meets the working duration constraint.
In a real worldIn the examples, phigh＝11，plowThe term 3 means that the part-time staff needs to work for 3-11 hours every day, that is, if a part-time staff is working on the day, the part-time staff needs to work for 3-11 hours, or does not work. Also, where the units are hours, if brought into the model, both need to be multiplied by 2, turning to the period for calculation.
The work hours per week for full-time employees are expressed as:
Figure BDA0002163653500000081
Figure BDA0002163653500000082
wherein f ishigh-weekAnd flow-weekThe unit is hour, 2 is multiplied to be converted into a time interval, and fi represents whether the full-time employee i needs to be on duty in one week, wherein the time interval needs to be 1, and the time interval does not need to be 0.
In one embodiment, flow-week＝38，fhigh-week45, the staff needs to work for 38-45 hours every week, namely if the staff is on duty, the staff needs to work for 38-45 hours, or the staff is not on duty.
The working days per week of the full-time staff are less than or equal to 6 days and are expressed as follows:
Figure BDA0002163653500000083
ftkithe formula shows that whether the k day full-time employee i is on duty, the duty is 1, and the duty is 0, and the formula shows that the day of duty of the full-time employee in one week should not be more than 6 days.
Full-time employees working in a dining session are provided with 1 session of dining time, expressed as:
Figure BDA0002163653500000084
Figure BDA0002163653500000085
where B is a set of meal periods, j ∈ B indicates that j belongs to a meal period, fbkijIndicating whether the full-time employee i schedules a meal in the jth time period on the kth day, wherein the scheduled meal is 1, and the scheduled meal is 0 if the full-time employee i does not schedule the meal; fs iskijRepresenting the planned working hour arrangement of the full-time employee i in the jth time period on the kth day, wherein the planned working hour is 1, and otherwise, the planned working hour is 0; len (b) indicates the length of the meal period, i.e. several periods are available for the staff to schedule a meal. The two constraints determine whether the full-time employee i meets the requirement of arranging the dining time, and if the full-time employee i meets the requirement, the dining time is arranged.
In one embodiment, the length of the meal period is 4, and for a full-time employee i, if there is no continuous work, such as fs, in the j ∈ B periodkijIn one time period j equals 0, other time periods j equals 1, where j ∈ B, then ∑ Ej∈Bfskij3, the constraint translates to Σj∈Bfbkij≥0，∑j∈BfbkijNot more than 0.09 due to fbkijIs a variable from 0 to 1, so fbkijCan only equal 0, meaning that the employee is not allocated dining time; on the contrary, when in the time period j epsilon B, the employee i continuously works, namely fskijAre all 1, the above constraints are converted into sigmaj∈Bfbkij≥1，∑j∈BfbkijAnd less than or equal to 1, namely the employee needs to be allocated with 1 time period of dining time.
A part-time employee working in a dining session is provided with a dining time of 1 session, expressed as:
Figure BDA0002163653500000092
the meanings of the two formulas are the same as the meanings of the dining time for providing 1 time interval for full-time employees working in the dining time interval, and are not repeated herein.
Full-time employees need to meet work continuity constraints, which are expressed as:
Figure BDA0002163653500000093
Figure BDA0002163653500000094
Figure BDA0002163653500000095
wherein fs iski1Whether the ith employee is on duty during the 1 st period for day k, fukijAnd fvkijAll intermediate variables are introduced by full-time staff meeting work continuity constraints.
In one embodiment, for example, for one day, a full-time employee needs to work on duty to satisfy the continuity constraint, assuming that S is 8 (the value of S in actual work is much larger, and a smaller value is taken here for convenience of explanation), the full-time employee needs to work for 4-6 hours per day, and for any full-time employee i, fs is usedijAnd the result shows that whether the full-time employee i is on duty in the jth time interval or not in one day, wherein the duty is 1 and the duty is 0. Fs if working continuity constraint needs to be satisfiedijThe values of (A) should be as follows:
Figure BDA0002163653500000096
Figure BDA0002163653500000101
that is, if a full-time employee satisfies the on-duty continuity constraint, then the following expression should be satisfied:
fsi1+|fsi2-fsi1|+|fsi3-fsi2|+…+|fsi8-fsi7|≤2
in the above expression, the absolute value seriously affects the operation speed of the model, and fu is introduced here in order to remove the absolute valueij，fvijTwo are providedIntermediate variables, which translate into the following 3 formulas:
Figure BDA0002163653500000102
Figure BDA0002163653500000103
Figure BDA0002163653500000104
the three formulas can ensure that the continuous work constraint is met when the staff goes to work one day, and although two intermediate variables are added, the model operation speed is improved by orders of magnitude. If the continuous work constraint of the one-week shift model staff is represented, only the variable k of the number of days is added on the basis, and the following steps are performed:
Figure BDA0002163653500000106
Figure BDA0002163653500000107
part-time employees need to meet work continuity constraints, expressed as:
Figure BDA0002163653500000108
Figure BDA0002163653500000109
Figure BDA0002163653500000111
wherein pski1For day k i employeeOn duty or off in the 1 st period, pukijAnd pvkijAll are intermediate variables introduced by the part-time staff meeting the working continuity constraint. The meaning of the continuous working constraint of the part-time staff is the same as that of the continuous working constraint of the full-time staff, and the specific implementation process of the embodiment is not explained.
Through the constraint conditions, the staff to be scheduled, which meets the constraint conditions and meets the staff demand, can be calculated from the staff to be scheduled.
The scheduling determination module 104 determines the optimal scheduling combination of the staff, which minimizes the human cost, according to the calculated objective function z used by the staff to be scheduled. The objective function z is the human cost, including the human cost of full-time employees and part-time employees. Preferably, the objective function is:
where k denotes the kth day, i denotes the ith employee, j denotes the jth period, Pr denotes the jth periodiRepresents the scheduling weight, ff, of the ith full-time employeekijIndicating whether the full-time employee i is on duty in the jth time interval on the kth day, wherein the duty is 1, and the duty is 0 if the full-time employee i is not on duty; pp (polypropylene)kijIndicating whether the part-time employee i on the kth day is on duty in the jth time period, wherein the duty is 1, and the duty is 0 if the part-time employee i is not on duty; wherein ff iskijAnd ppkijMeal periods have been deducted for significant hours. ftkiIndicating whether the full-time employee i on the kth day is on duty or not, wherein the on duty is 1, and the off duty is 0; pt iskiIndicating whether the day i of the part-time employee on the kth day is on duty, wherein the duty is 1, and the duty is 0 if the day i is not on duty; the coefficient theta is a weight coefficient for the working hours and the number of the people of the part-time staff, so that the model can preferentially select the full-time staff for scheduling. The scheduling weight of full-time employees and the weight coefficient of part-time employees are preset.
In one embodiment, K is 7, N is 4, M is 4, and S is 28. The specific meaning of the objective function is that the result should be minimized, including the total working hours of the full-time employees in one week, the total working hours of the part-time employees in one week, the weight coefficient of the part-time employees, the number of the full-time employees in the week, and the number of the part-time employees in the week.
The objective functions and models described above can be solved using any suitable known solver.
The output module 105 is used for outputting the scheduling data according to the determined optimal staff scheduling combination.
In another embodiment, the store shift scheduling system further comprises a checking module for checking whether the optimal shift scheduling combination of the employee meets the requirements after outputting the shift scheduling data. For example, whether the scheduling result meets the requirement is detected, and whether the scheduling data violates the scheduling priority constraint condition of full-time employees is mainly detected. For example, the employee is configured with two kinds of full-time employees and part-time employees, the employees are subdivided into 8 post levels, the priority of the post 1, the post 2, the post 3, the post 4, the post 5, the post 6, the post 7 and the post 8 is reduced in sequence, and the priority of the 8 posts is PriAnd if the staff with the higher priority cannot meet the manpower requirement of the store, replenishing the staff with the higher priority, and sequentially performing the steps.
FIG. 2 shows a flow diagram of an embodiment of a store scheduling method according to the invention, the method comprising: step S201, responding to the received scheduling instruction, and receiving the staff demand of each time period of the store; step S202, pre-stored staff to be scheduled and the working time period of the staff to be scheduled are obtained; step S203, determining staff to be scheduled meeting preset constraint conditions; step S204, determining the optimal scheduling combination of the staff, which meets the staff demand and minimizes the labor cost, according to the determined staff to be scheduled and the labor cost objective function; and S205, outputting the scheduling data according to the determined optimal scheduling combination of the employees.
The particular features, structures, or characteristics of the various embodiments described herein may be combined as suitable in one or more embodiments of the invention.
As used herein, the singular forms "a", "an" and "the" include plural references (i.e., have the meaning "at least one"), unless the context clearly dictates otherwise. It will be further understood that the terms "has," "includes" and/or "including," when used in this specification, specify the presence of stated features, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, operations, elements, components, and/or groups thereof. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
The foregoing describes some preferred embodiments of the present invention, but it should be emphasized that the invention is not limited to these embodiments, but can be implemented in other ways within the scope of the inventive subject matter. The present invention can be modified and modified by those skilled in the art without departing from the scope of the present invention, and the modified and modified embodiments are also within the scope of the present invention.

Claims (10)

1. An out-of-store scheduling system, the system comprising:
the receiving module is used for responding to the received scheduling instruction and receiving the staff demand of each time period of the store;
the acquisition module is used for acquiring prestored staff to be scheduled and the working time period of the staff;
the constraint module is used for determining staff to be scheduled meeting preset constraint conditions;
the scheduling determining module is used for determining the optimal scheduling combination of the staff, which meets the staff demand and minimizes the labor cost, according to the determined staff to be scheduled and the labor cost objective function;
and the output module is used for outputting the scheduling data according to the determined optimal staff scheduling combination.
2. The store scheduling system of claim 1 wherein the predetermined constraints comprise one or more of: productivity constraints, people number constraints, and man-hour constraints.
3. The store scheduling system of claim 1 wherein the human cost is a sum of a full-time employee on-duty time, a part-time employee weight, a part-time employee on-duty time, a full-time employee on-duty number, and a part-time employee weight, a part-time employee on-duty number, the scheduling determination module determines the optimal scheduling combination for the employee based on an objective function of:
wherein: n is the number of full-time members of the store, M is the number of part-time members of the store, S is the total number of scheduling periods of one day, K is the number of days of the week, K is the kth day, i is the ith staff, j is the jth period, Pr is the number of daysiRepresenting the scheduling weight of the ith full-time employee; ff (a)kijIndicating whether the full-time employee i is on duty in the jth time interval on the kth day, wherein the duty is 1, and the duty is 0 if the full-time employee i is not on duty; pp (polypropylene)kijIndicating whether the part-time employee i on the kth day is on duty in the jth time period, wherein the duty is 1, and the duty is 0 if the part-time employee i is not on duty; ftkiIndicating whether the full-time employee i on the kth day is on duty or not, wherein the on duty is 1, and the off duty is 0; pt iskiIndicating whether the day i of the part-time employee on the kth day is on duty, wherein the duty is 1, and the duty is 0 if the day i is not on duty; the coefficient θ is a weighting coefficient of the part-time employee.
4. The store scheduling system of claim 2, wherein the constraints module comprises a productivity constraints sub-module that determines whether the staff to be scheduled at each time period has a human effort greater than or equal to the staff demand at the corresponding time period.
5. The store scheduling system of claim 2, wherein the restriction module comprises a people restriction sub-module that determines whether the number of people on duty is met during the same time period and whether the number of people on duty is met during the same time period.
6. The store scheduling system of claim 2, wherein the constraint module comprises a man-hour constraint sub-module that determines whether one or more of the following conditions are met:
1) the working hours of the full-time staff every day are [ f ]low,fhigh]To (c) to (d);
2) the working hours of the part-time staff every day are [ p ]low,phigh]To (c) to (d);
3) the working hours of the full-time staff are in every weeklow-week,fhigh-week]To (c) to (d);
4) the working days of the full-time staff per week are less than or equal to the preset days;
5) providing the staff working in the dining time period with the dining time of at least 1 time period;
6) the full-time staff and the part-time staff meet the working continuity constraint condition;
wherein f ishighRepresents the longest working time of the full-time employee in the day, flowRepresents the shortest working time of the full-time staff in the day, phighRepresents the longest working time of the part-time employee in the day, plowIndicating the shortest working time of the part-time employee in the day, flow-weekRepresents the shortest working time of the full-time employee in one week, fhigh-weekRepresenting the longest working time of a full-time employee in a week.
7. The store scheduling system of claim 6, wherein the man-hour constraint sub-module determines whether full-time employees or part-time employees meet the requirements for scheduled meal times by the following formula:
Figure FDA0002163653490000021
Figure FDA0002163653490000022
for a full-time employee,for the part-time employees, the employee is,
Figure FDA0002163653490000024
where B is a set of meal periods, j ∈ B indicates that j belongs to a meal period,bkijindicating whether the employee i schedules a meal in the jth time period on the kth day, wherein the scheduled meal is 1, and the non-scheduled meal is 0; skijRepresenting the planned working hour arrangement of the employee i in the jth time period on the kth day, wherein the planned working hour is 1, and otherwise, the planned working hour is 0; len (b) indicates the length of the meal period.
8. The store scheduling system of claim 6, wherein the man-hour constraint sub-module determines whether a full-time employee or a part-time employee meets a work continuity constraint by:
Figure FDA0002163653490000031
skij-ski(j-1)+ukij-vkij＝0,j≥2
ukij+vkij≤1,j≥2
for a full-time employee,
Figure FDA0002163653490000032
for the part-time employees, the employee is,
Figure FDA0002163653490000033
wherein s iski1Whether the ith employee is on duty in the 1 st period for the kth day, ukijAnd vkijAre all intermediate variables introduced.
9. The store scheduling system of claim 1, further comprising:
and the checking module is used for checking whether the optimal shift combination of the staff meets the requirements after the shift data is output.
10. A method for shop scheduling, the method comprising:
receiving staff demand of each time period of the store in response to the received scheduling instruction;
acquiring pre-stored staff to be scheduled and the working time period thereof;
determining staff to be scheduled which meet preset constraint conditions;
determining an optimal scheduling combination of the staff, which meets the staff demand and minimizes the labor cost, according to the determined staff to be scheduled and the labor cost objective function;
and outputting scheduling data according to the determined optimal scheduling combination of the employees.
CN201910740157.0A 2019-08-12 2019-08-12 Shop scheduling system and method Pending CN110705815A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910740157.0A CN110705815A (en) 2019-08-12 2019-08-12 Shop scheduling system and method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910740157.0A CN110705815A (en) 2019-08-12 2019-08-12 Shop scheduling system and method

Publications (1)

Publication Number Publication Date
CN110705815A true CN110705815A (en) 2020-01-17

Family

ID=69193274

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910740157.0A Pending CN110705815A (en) 2019-08-12 2019-08-12 Shop scheduling system and method

Country Status (1)

Country Link
CN (1) CN110705815A (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112381261A (en) * 2020-09-17 2021-02-19 苏州盖雅信息技术有限公司 Flexible employment shift demand release system and calculation method
CN114496179A (en) * 2020-10-27 2022-05-13 贵阳朗玛信息技术股份有限公司 Method and device for intelligent scheduling management of medical personnel
CN115271372A (en) * 2022-07-04 2022-11-01 无锡喔趣信息科技有限公司 Human resource scheduling management system and method based on regional linkage
CN116670698A (en) * 2021-04-09 2023-08-29 全球大门股份有限公司 Cleaning service support server, cleaning service support method, and computer-readable storage medium

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105868840A (en) * 2016-03-12 2016-08-17 丽水学院 Flexible service scheduling system and method capable of adjusting window-opening number in real time
CN105894241A (en) * 2016-03-12 2016-08-24 丽水学院 Inverted-triangle-based mixed shift arrangement system and method for flexible service system
CN106548274A (en) * 2016-10-19 2017-03-29 平安科技（深圳）有限公司 A kind of personnel's scheduling method and device
CN109583840A (en) * 2018-11-27 2019-04-05 重庆太事齐科技有限公司 A kind of scheduling method, device and equipment

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105868840A (en) * 2016-03-12 2016-08-17 丽水学院 Flexible service scheduling system and method capable of adjusting window-opening number in real time
CN105894241A (en) * 2016-03-12 2016-08-24 丽水学院 Inverted-triangle-based mixed shift arrangement system and method for flexible service system
CN106548274A (en) * 2016-10-19 2017-03-29 平安科技（深圳）有限公司 A kind of personnel's scheduling method and device
CN109583840A (en) * 2018-11-27 2019-04-05 重庆太事齐科技有限公司 A kind of scheduling method, device and equipment

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112381261A (en) * 2020-09-17 2021-02-19 苏州盖雅信息技术有限公司 Flexible employment shift demand release system and calculation method
CN114496179A (en) * 2020-10-27 2022-05-13 贵阳朗玛信息技术股份有限公司 Method and device for intelligent scheduling management of medical personnel
CN116670698A (en) * 2021-04-09 2023-08-29 全球大门股份有限公司 Cleaning service support server, cleaning service support method, and computer-readable storage medium
CN115271372A (en) * 2022-07-04 2022-11-01 无锡喔趣信息科技有限公司 Human resource scheduling management system and method based on regional linkage
CN115271372B (en) * 2022-07-04 2023-09-12 无锡喔趣信息科技有限公司 Human resource scheduling management system and method based on regional linkage

Similar Documents

Publication Publication Date Title
CN110705815A (en) Shop scheduling system and method
US5913201A (en) Method and apparatus for assigning a plurality of work projects
US10970682B1 (en) System and method for agent scheduling using mixed integer linear programming
US20060167731A1 (en) Automatically scheduling meetings
Wang et al. Nurse absenteeism and staffing strategies for hospital inpatient units
CN110751358A (en) Scheduling method for airport ground service personnel, electronic equipment and storage medium
Rahardja et al. Model Scheduling Optimization Workforce Management Marketing
CN112348368A (en) Automatic scheduling and intelligent scheduling system for aviation ground service
Mabert et al. The detail scheduling of a part‐time work force: A case study of teller staffing
CN114782030A (en) Intelligent management system and method based on big data project
CN116341868A (en) Method and system for optimally assigning airport ground aircraft station-crossing guarantee tasks
Chen et al. Short-term manpower planning for MRT carriage maintenance under mixed deterministic and stochastic demands
Al-Sultan Airport check-in optimization by IP and simulation in combination
Farahani et al. Flexible personnel scheduling in large multi-product unpaced asynchronous assembly lines
CN112749942A (en) Scheduling method, device, equipment and storage medium
Liu The optimization of worker's quantity based on cross-utilization in two departments
CN115330195A (en) Periodic scheduling method and device, electronic equipment and storage medium
Edna Chan et al. Operations research methods applied to workflow in a medical records department
Chua et al. Multi-skilled manpower scheduling with part-time consideration: Case study
Cavada et al. A workforce planning and allocation model for the outbound baggage loading area at Santiago International Airport
Qian et al. School bus routing with bell time policy optimization: a multi-objective approach
Noor et al. A Mixed Integer Linear Programming Model for Crew Scheduling At Fast Food Restaurant
Korneev et al. An Algorithm for the Distribution of Performers by Work, Taking Into Account the Priority of Tasks and the Specifics of the Necessary Skills
Easton Staffing, cross-training, and scheduling with cross-trained workers in extended-hour service operations
Zhang et al. Equipment scheduling problem under disruptions in mail processing and distribution centres

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
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20200117