Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care

Liu, Ran; Xie, Xiaolan; Augusto, Vincent; Rodríguez, Carlos Sánchéz

doi:10.1016/j.ejor.2013.04.044

Cited by 241 publications

(113 citation statements)

References 67 publications

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“…Another important variation of the VRP is the Distance-Constrained (DC-VRP) that involves a real-life feature as the maximum distance that a vehicle is available to drive or the labor period, however some studies are dedicated to this constraint (Almoustafa et al, 2013;Kek et al, 2008;Nagarajan & Ravi, 2012;Tlili et al, 2014). On the other hand, the pickup and delivery constraint is generally combined with VRPTW (Fikar & Hirsch, 2015;Küçükoğlu & Öztürk, 2015;Lin, 2011;Liu et al, 2013;López-Santana & Romero Carvajal, 2015). The MP-VRP (multi-period VRP) considers a planning horizon where the customers need to be visited several times with periodic or non-periodic frequency according to the service operation.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

A hybrid expert system, clustering and ant colony optimization approach for scheduling and routing problem in courier services

López-Santana¹,

Rodríguez-Vásquez²,

Méndez-Giraldo³

2018

10.5267/j.ijiec

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This paper focuses on the problem of scheduling and routing workers in a courier service to deliver packages for a set of geographically distributed customers and, on a specific date and time window. The crew of workers has a limited capacity and a time window that represents their labor length. The problem deals with a combination of multiples variants of the vehicle routing problem as capacity, multiple periods, time windows, due dates and distance as constraints. Since in the courier services the demands could be of hundreds or thousands of packages to be delivered, the problem is computationally unmanageable. We present a threephase solution approach. In the first phase, a scheduling model determines the visit date for each customer in the planning horizon by considering the release date, due date to visit and travel times. We use an expert system based on the know-how of the courier service, which uses an inference engine that works as a rule interpreter. In the second phase, a clustering model assigns, for each period, customers to workers according to the travel times, maximum load capacity and customer's time windows. We use a centroid based and sweep algorithms to solve the resulted problem. Finally, in the third phase, a routing model finds the order in which each worker will visit all customers taking into account their time windows and worker's available time. To solve the routing problem we use an Ant Colony Optimization metaheuristic. We present some numerical results using a case study, in which the proposed method of this paper finds better results in comparison with the current method used in the case study.

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Section: Background and Literature Reviewmentioning

confidence: 99%

A hybrid expert system, clustering and ant colony optimization approach for scheduling and routing problem in courier services

López-Santana¹,

Rodríguez-Vásquez²,

Méndez-Giraldo³

2018

10.5267/j.ijiec

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“…A tabu method, a genetic algorithm based on chromosome permutation, a "split" procedure and a local search are proposed by [9] to solve a particular problem of PDPTW. This Problem considers several requests: the delivery of medicines and medical care pharmacy at home patients and the pick-up of biological samples and unused drugs at the patients.…”

Section: Genetic Algorithm For the Vehicle Routing Problem And The Pimentioning

confidence: 99%

A Comparative Study of the PSO and GA for the m-MDPDPTW

Alaïa

Dridi

Borne³

et al. 2018

INT J COMPUT COMMUN

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Abstract:The m-MDPDPTW is the multi-vehicles, multi-depots pick-up and delivery problem with time windows. It is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers for the purpose of satisfying precedence, capacity and time constraints. This problem is a very important class of operational research, which is part of the category of NP-hard problems. Its resolution therefore requires the use of evolutionary algorithms such as Genetic Algorithms (GA) or Particle Swarm Optimization (PSO). We present, in this sense, a comparative study between two approaches based respectively on the GA and the PSO for the optimization of m-MDPDPTW. We propose, in this paper, a literature review of the Vehicle Routing Problem (VRP) and the Pick-up and Delivery Problem with Time Windows (PDPTW), present our approaches, whose objective is to give a satisfying solution to the m-MDPDPTW minimizing the total distance travelled. The performance of both approaches is evaluated using various sets instances from [10] PDPTW benchmark data problems. From our study, in the case of m-MDPDPTW problem, the proposed GA reached to better results compared with the PSO algorithm and can be considered the most appropriate model to solve our m-MDPDPTW problem.

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“…After the first work by Min (1989), growing concerns are paid on this topic, e.g., Cao and Lai, 2007;Ai and Kachitvichyanukul, 2009;Catay, 2010;Lai and Cao 2010;Subramanian, et al, 2011;Hezer and Kara, 2011;Jun and Kim, 2012;Goksal, Karaoglan and Altiparmak, 2013;Liu, et al, 2013;Gribkovskaia, Laporte and Vlcek, 2007. These are all single-depot and non-Weber basis problems.…”

Section: Introductionmentioning

confidence: 99%

“…The major aim of this study is to reveal some properties of VRPSPD especially interested in comparison with separate transportation and centralized network configuration. To One of the recent studies on VRP is an extension from the generic customer demand satisfaction and vehicle payload (Liu and Xie, 2013). The other concerns have been paid to multi-depot problem (Chen, Imai and Zhao, 2005;Crevier, Cordeau, andLaporte, 2007, Shimizu andSakaguchi, 2014 b) and multi-objective formulation (Jozefowiez, Semet and Talbi, 2008).…”

Section: Introductionmentioning

confidence: 99%

A hybrid method for solving multi-depot VRP with simultaneous pickup and delivery incorporated with Weber basis saving heuristic

Shimizu

Sakaguchi

Yoo

2016

JAMDSM

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Under growing concerns with sustainability in global and changing market, establishing a cooperative and competitive logistic is becoming a keen issue to provide manufacturing systems amenable to sales and operations planning. As a deployment for such practice, we have engaged in the various studies on logistics optimization. Especially, noticing that transportation cost and/or CO 2 emission actually depend not only on distance but also loading weight (Weber basis), we have recently developed a few hybrid meta-heuristic methods for vehicle routing problems (VRP) and shown their effectiveness through numerical experiments. To the best of our knowledge, however, there exist no studies that take the Weber basis into account on VRP except for ours. As a hot interest in this area, we pay our attention on VRP with simultaneous pickup and delivery (VRPSPD). Then, this study attempts to extend the foregoing Weber basis study under single depot to multi-depot problem and intends to reveal some properties of VRPSPD. To work with such concerns, we have developed a novel hierarchical method comprised of a modified tabu search, a graph algorithm for the minimum cost flow problem and a Weber basis saving method. The proposed method is possible to solve various real world applications practically even with large problem sizes. Finally, the effectiveness of the proposed method is validated through numerical experiments taken place from various viewpoints to discuss about some peculiar features of VRPSPD.Key words : Multi-depot VRPSPD, Hybrid approach, Weber basis saving method, Graph algorithm, Modified tabu search IntroductionUnder growing concerns with sustainability in global and changing market, establishing a cooperative and competitive logistic is becoming a keen issue to provide manufacturing systems amenable to sales and operations planning (SOP). As a deployment for such practice, we have engaged in various studies on logistics optimization. Especially, noticing that transportation cost and/or CO 2 emission actually depend not only on distance but also loading weight (tonnage-kilo meter basis), we have recently developed a few hybrid meta-heuristic methods for vehicle routing problem (VRP) and shown their effectiveness through numerical experiments. Though this tonnage-kilo meter basis transportation cost accounting is generally known as Weber basis and popularly applied to facility location problems, it has never been considered in VRP previously. However, we will agree this idea is quite relevant if we only show such facts that reducing weight of vehicle body has been a keen interest in car industry and Japanese government recommend to use the improved tonnage-kilo meter basis, i.e., Weber basis to evaluate the amount of CO 2 emission from vehicles.As a growing interest of VRP associated with SOP, we recently concerned simultaneous pickup and delivery for single depot VRP (VRPSPD) associated with the Weber basis and its generalized one Sakaguchi, 2014 a, 2015). To cope with more relevant and realistic scene...

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Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care

Cited by 241 publications

References 67 publications

A hybrid expert system, clustering and ant colony optimization approach for scheduling and routing problem in courier services

A hybrid expert system, clustering and ant colony optimization approach for scheduling and routing problem in courier services

A Comparative Study of the PSO and GA for the m-MDPDPTW

A hybrid method for solving multi-depot VRP with simultaneous pickup and delivery incorporated with Weber basis saving heuristic

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