Solving a multi-objective dynamic stochastic districting and routing problem with a co-evolutionary algorithm

Lei, Hongtao; Wang, Rui; Laporte, Gilbert

doi:10.1016/j.cor.2015.09.002

Cited by 62 publications

(38 citation statements)

References 55 publications

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“…The objectives are the same as in Lei et al (2015), but instead of using a weighted sum as the objective function, the authors treat the problem as a true multi-objective optimization problem and solve it with a multi-objective evolutionary algorithm. Although the problems in Lei et al (2015) and Lei et al (2016) consider a multi-period planning horizon, they do not contain a scheduling component comparable to the MPSTDP-S. In Lei et al (2015), the service days within 190 each period must be decided, but, in contrast to the MPSTDP-S, each customer must be served exactly once per period and, hence, there are no restrictions on the temporal distribution of visits.…”

Section: Related Workmentioning

confidence: 99%

The multi-period service territory design problem – An introduction, a model and a heuristic approach

Bender

Meyer

Kalcsics

et al. 2016

Transportation Research Part E: Logistics and Transportation Re

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In service territory design applications, a field service workforce is responsible for providing recurring services at their customers' sites. We introduce the associated planning problem, which consists of two subproblems:In the partitioning subproblem, customers must be grouped into service territories. In the scheduling subproblem, customer visits must be scheduled throughout the multi-period planning horizon. The emphasis of this paper is put on the scheduling subproblem. We propose a mixed integer programming model for this subproblem and present a location-allocation heuristic. The results of extensive experiments on real-world instances show that the proposed heuristic produces high-quality solutions.Keywords: territory design, multi-period planning horizon, mixed integer linear programming, location-allocation heuristic 2010 MSC: 90B06, 90B80, 90C59

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Section: Related Workmentioning

confidence: 99%

The multi-period service territory design problem – An introduction, a model and a heuristic approach

Bender

Meyer

Kalcsics

et al. 2016

Transportation Research Part E: Logistics and Transportation Re

View full text Add to dashboard Cite

show abstract

“…One of their main contributions is the derivation of analytical expressions to determine the optimal number of service districts for the US postal system. A methodology to design multidelivery tours associated with the servicing of an urban region of irregular shape is presented in [15]. The authors' methodology is based on a sweep approach and assumes a rectangular grid structure.…”

Section: Literature Reviewmentioning

confidence: 99%

“…They presented a Tabu Search (TS) and multistart heuristics to solve the problem. Also, a multiobjective dynamic stochastic districting and routing problem is considered in [15]. In this problem, the customers of a territory Mathematical Problems in Engineering 3 stochastically evolve over the planning periods.…”

Section: Literature Reviewmentioning

confidence: 99%

A GRASP‐Tabu Heuristic Approach to Territory Design for Pickup and Delivery Operations for Large‐Scale Instances

González-Ramírez

Smith

Askin

et al. 2017

Mathematical Problems in Engineering

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We address a logistics districting problem faced by a parcel company whose operations consist of picking up and delivering packages over a service region. The districting process aims to find a partition of the service region into delivery and collection zones that may be served by a single vehicle that departs from a central depot. Criteria to be optimized are to balance workload content among the districts and to create districts of compact shape. A solution approach based on a hybrid procedure that combines elements of GRASP and Tabu Search (TS) is proposed to solve large-scale instances. Numerical experimentation is performed considering different instance sizes and types. Results show that the proposed solution approach is able to solve large-scale instances in reasonable computational times with good quality of the solutions obtained. To determine the quality of the solutions, results are compared with CPLEX solutions and with the current real solution to highlight the benefits of the proposed approach. Conclusions and recommendations for further research are provided.

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“…This model uses a goal programming approach to address this aim and calculates server workload with an AH model developed by Burwell [39]. Lei et al [51] formulated a four-objective model for a districting-routing problem under dynamic and stochastic conditions. They solved this model by a two-stage stochastic programming approach and an enhanced multi-objective evolutionary algorithm.…”

Section: Single Dispatch Total Backup and Non-homogeneous Serversmentioning

confidence: 99%

“…Constraint (51) calculates jm  , where its denominator shows the probability that all servers are not busy. Constraint (51) shows the set of flow-balancing equations, which compute the probability of states. Actually, these equations are the modified versions of the original HQM [2] to take into account different service rates for inter-district and intra-district customers.…”

Section: Location Models and Solution Approachesmentioning

confidence: 99%

Hypercube Queuing Models in Emergency Service Systems: A State-of-the-Art Review

2018

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Abstract. This study provides a review of hypercube queuing models (HQMs) in emergency service systems (ESSs). This survey presents a comprehensive review and taxonomy of models, solutions and applications related to the HQM after Larson [12]. In addition, the structural aspects of HQMs are examined. Important contributions of the existing research are addressed by taking into account multiple factors. In particular, the integration of location decisions with HQMs for designing an ESS is discussed. Finally, a list of issues for future studies are presented.

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Solving a multi-objective dynamic stochastic districting and routing problem with a co-evolutionary algorithm

Cited by 62 publications

References 55 publications

The multi-period service territory design problem – An introduction, a model and a heuristic approach

The multi-period service territory design problem – An introduction, a model and a heuristic approach

A GRASP‐Tabu Heuristic Approach to Territory Design for Pickup and Delivery Operations for Large‐Scale Instances

Hypercube Queuing Models in Emergency Service Systems: A State-of-the-Art Review

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