A two-phase hybrid heuristic algorithm for the capacitated location-routing problem

Escobar, John Willmer; Linfati, Rodrigo; Toth, Paolo

doi:10.1016/j.cor.2012.05.008

Cited by 130 publications

(76 citation statements)

References 29 publications

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“…Thus the Last Mile delivery problem has recently garnered a great deal of attention from the government and all the stakeholders of e-commerce supply chain. one can find ant colony optimization (ACO) [32], genetic algorithm(GA) [33,34], simulated annealing (SA) [13,35], simulated annealing with variable neighborhood search (SA-VNS) [18], local search (LS) [20], greedy randomized adaptive search with evolutionary local search (GRASP+ELS) [36], granular tabu search (GTS) [37], granular tabu search with variable neighborhood search (GVTNS) [38], multi-start iterated local search with tabu list and path relinking (MS-ILS) [31] and multi-start simulated annealing heuristic (MSA) [21]. The most related methods are the metaheuristics hybrid with GA and LS.…”

Section: Introductionmentioning

confidence: 99%

Location-Routing Problem with Simultaneous Home Delivery and Customer’s Pickup for City Distribution of Online Shopping Purchases

Zhou

Wang

et al. 2016

Sustainability

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Abstract:With the increasing interest in online shopping, the Last Mile delivery is regarded as one of the most expensive and pollutive-and yet the least efficient-stages of the e-commerce supply chain. To address this challenge, a novel location-routing problem with simultaneous home delivery and customer's pickup is proposed. This problem aims to build a more effective Last Mile distribution system by providing two kinds of service options when delivering packages to customers. To solve this specific problem, a hybrid evolution search algorithm by combining genetic algorithm (GA) and local search (LS) is presented. In this approach, a diverse population generation algorithm along with a two-phase solution initialization heuristic is first proposed to give high quality initial population. Then, advantaged solution representation, individual evaluation, crossover and mutation operations are designed to enhance the evolution and search efficiency. Computational experiments based on a large family of instances are conducted, and the results obtained indicate the validity of the proposed model and method.

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Section: Introductionmentioning

confidence: 99%

Location-Routing Problem with Simultaneous Home Delivery and Customer’s Pickup for City Distribution of Online Shopping Purchases

Zhou

Wang

et al. 2016

Sustainability

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“…In this study, we have considered small values of . The four operations considered to generate granular neighborhoods were insertion, double insertion, exchange, and double exchange [24,25].…”

Section: Granular Neighborhoodsmentioning

confidence: 99%

“…, , and are given parameters. Successful applications of the idea of granularity to different vehicle routing problems can be consulted in [23][24][25][26][27][28][29][30].…”

Section: A Granular Space Searchmentioning

confidence: 99%

Comparative analysis of granular neighborhoods in a Tabu Search for the vehicle routing problem with heterogeneous fleet and variable costs (HFVRP)

2017

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In the vehicle routing problem with heterogeneous fleet and variable costs (HFVRP), the group of routes to be developed to satisfy the demand of the customer must be determined, considering the minimization of the total costs of the travelled distance. Heuristic algorithms based on local searches use simple movements (neighborhoods) to generate feasible solutions to problems related to route design. In this article, we conduct a comparative analysis of granular neighborhoods in a Tabu Search for the HFVRP, in terms of the quality of the obtained solution. The computational experiments, performed on instances of benchmarking for the HFVRP, showed the efficiency and effectiveness of implementing some neighborhoods in metaheuristic algorithms of path, such as the Tabu Search.

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“…In Prodhon and Prins (2014), the authors present a complete study of LRP, analyzing and classifying different variants of the problem. The LRP has been solved with matheuristics techniques, combining heuristics and exact methods (Contardo et al, 2014), (Escobar et al, 2013), (Prins et al, 2007), (Ting & Chen, 2013). These methods have been applied to instances with up 200 clients.…”

Section: Literature Reviewmentioning

confidence: 99%

Introducing radiality constraints in capacitated location-routing problems

Ocampo¹,

Guimarães²,

Rendón³

2017

10.5267/j.ijiec

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In this paper, we introduce a unified mathematical formulation for the Capacitated Vehicle Routing Problem (CVRP) and for the Capacitated Location Routing Problem (CLRP), adopting radiality constraints in order to guarantee valid routes and eliminate subtours. This idea is inspired by formulations already employed in electric power distribution networks, which requires a radial topology in its operation. The results show that the proposed formulation greatly improves the convergence of the solver.

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A two-phase hybrid heuristic algorithm for the capacitated location-routing problem

Cited by 130 publications

References 29 publications

Location-Routing Problem with Simultaneous Home Delivery and Customer’s Pickup for City Distribution of Online Shopping Purchases

Location-Routing Problem with Simultaneous Home Delivery and Customer’s Pickup for City Distribution of Online Shopping Purchases

Comparative analysis of granular neighborhoods in a Tabu Search for the vehicle routing problem with heterogeneous fleet and variable costs (HFVRP)

Introducing radiality constraints in capacitated location-routing problems

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