A hybrid Constraint Programming/Mixed Integer Programming framework for the preventive signaling maintenance crew scheduling problem

Pour, Shahrzad M.; Drake, John H.; Ejlertsen, Lena Secher; Rasmussen, Kourosh Marjani; Burke, Edmund K.

doi:10.1016/j.ejor.2017.08.033

Cited by 56 publications

(14 citation statements)

References 16 publications

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“…Due to a large number of infeasible solutions in a cyclic shifting, a method of modeling scheduling problems with mixed integer programming is studied. Pour et al [16] proposed a hybrid framework for staff shifting problem, they implemented the global constraint programming model to find the (near)optimal solutions. Compared with constraint programming, this model can produce better solutions by taking the requirements of staff into consideration.…”

Section: Related Workmentioning

confidence: 99%

A MOEAD-Based Approach to Solving the Staff Scheduling Problem

Hong¹,

Chen²,

Cao³

et al. 2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Due to the impact on increase of the utilization efficiency of the staff and decrease of operating cost of enterprises, the staff scheduling problem has attracted the interests of many scholars. Actually, the staff scheduling problem can be considered to be how to assign the right staff to the right shift on the right time period based on constraints, meanwhile the objectives should be optimized. Hence, designing an algorithm to satisfy all the requirements mentioned above is challenging. First, there are prohibitive combinations of assigning the staff to shifts from a sheer numbers perspective; Next, there are potential conflicts among optimization objectives, which means objectives may not reach the optimization at the same time and the optimal schedule can not be found; Finally, rare work about the fairness of optimization objectives has been studied. The existing works usually focus on optimization objectives in total, ignoring the fairness of them. A schedule with best optimization objectives can not provide the highest fairness. Hence, we propose an approach based on multi-objective evolutionary algorithm based on decomposition (MOEAD) to solve the staff scheduling problem in the fairness aspect. A series of experiments are performed and prove that the proposed method can effectively find the schedule with fairness.

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Section: Related Workmentioning

confidence: 99%

A MOEAD-Based Approach to Solving the Staff Scheduling Problem

Hong¹,

Chen²,

Cao³

et al. 2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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“…Many researchers have studied the crew scheduling problem as an attractive and frequently observed problem in transport (Giachetti et al 2013;Duque et al 2016;Bach et al 2016;Zhou et al 2016;Pour et al 2018;Wang et al 2018, Boyer et al 2018. Scheduling problems in air transport industry refer to aircraft crew and ground crew scheduling.…”

Section: Background and Related Workmentioning

confidence: 99%

Control Model for Ground Crew Scheduling Problem at Small Airports: Case of Serbia

et al. 2021

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Present-day airline industry is quite a competitive field and crew scheduling represents one of the crucial problems due to significant impact on the airline’s cost. The crew scheduling problem is based on the assignment of crew members to operate different tasks of route. The main goal of this paper is to provide an analysis and a solution to one of the biggest problems detected on a small airport in the Serbia - the problem of ground crew scheduling. The paper presents the main characteristics, goals and limitations of a real-life problem identified at this small airport. In order to solve the problem, we developed a dynamic discrete simulation model. The model is developed in a spreadsheet environment of Microsoft Excel. Some of the main limitations found in the development of the model are strong constraints and multiple goals. The model presented in the paper is designed as a useful management tool for smaller airports and is aimed at the improvement of operative processes.

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“…Meng et al [43] and Lunardi et al [44] performed a comparison between CP and mixed-integer linear programming to minimize the make-span in a shop scheduling problem. Pour et al [45] combined hybrid approaches of constraint programming and mixed-integer programming to develop an initial feasible solution-the "warm start" solution. This model was applied in the Danish railway system and produced significant initial solutions for solving large-scale scheduling problems.…”

Section: Literature Reviewmentioning

confidence: 99%

Two-Stage Optimization Model for Life Cycle Maintenance Scheduling of Bridge Infrastructure

2020

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As bridge infrastructure ages, the deterioration of materials and hazard events reduce the service quality and compromise the safety of the structure. Therefore, there is a tremendous need for bridge maintenance planning, and such maintenance studies during recent years have focused on the life cycle aspect. To fulfill the budget requirements of life cycle maintenance, an important issue is to ensure that the limited maintenance budget is utilized in an effective way. However, there are few studies that have aimed to assess the topic of budget allocation and the adjustment of bridge life-cycle maintenance issues. In order to resolve such issues, a two-stage optimization model based on constraint programming (CP) is proposed in this study to deal with maintenance scheduling problems. This is facilitated by adopting the resource-constrained project scheduling problem (RCPSP) framework, in which, three plans according to the maintenance time point are considered (i.e., early, middle, and late plans). According to the RCPSP concepts, this study views the budget ceiling as the resource limit, and maintenance plans as activities, so that the feasibility of each maintenance plan depends on the sufficiency of the budget. As the first stage, Model-I (the life cycle lifespan evaluation model) takes a life cycle perspective, evaluating how long it will take to keep all bridges in a serviceable condition with minimum expenditure over the planning cycle, and evaluates the annual budgets that can be used as a reference for users to draft a budget plan. Based on the planning result from Model-I and the actual annual budget approved for the current year, the second stage, Model-II (the annual budget allocation model) then reallocates the actual budget to take into account the importance of all bridges and different costs and benefits of maintenance plans, and revises the suggested annual budget values obtained by Model-I for the following years. Through a case study, the optimized result demonstrates that annual recursive implementation of this two-stage model satisfies the need to adjust existing budgetary data, and provides management personnel with optimized and realistic maintenance decision support for bridge infrastructure.

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A hybrid Constraint Programming/Mixed Integer Programming framework for the preventive signaling maintenance crew scheduling problem

Cited by 56 publications

References 16 publications

A MOEAD-Based Approach to Solving the Staff Scheduling Problem

A MOEAD-Based Approach to Solving the Staff Scheduling Problem

Control Model for Ground Crew Scheduling Problem at Small Airports: Case of Serbia

Two-Stage Optimization Model for Life Cycle Maintenance Scheduling of Bridge Infrastructure

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