A priori policy evaluation and cyclic-order-based simulated annealing for the multi-compartment vehicle routing problem with stochastic demands

Goodson, Justin

doi:10.1016/j.ejor.2014.09.031

Cited by 35 publications

(17 citation statements)

References 23 publications

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“…of the CVRP tend to be random or stochastic, giving rise to the stochastic vehicle routing problem (SVRP). We found that most researches mainly focused on VRPSD, where customer demands are known only when the vehicle arrives to location [28][29][30][31][32][33][34][35]. In the following, some studies will be mentioned.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A paired cooperative optimization strategy is developed for the VRPSD with split delivery [31]. But, the constraint for the visiting time of customers is not considered in these studies [28][29][30][31][32][33][34]. However, to be closer to the practice, Tan et al [35] and Lei et al [19] applied a soft time windows constraint for the VRPSD, which means that vehicles may be violated if the arrival time at the location of customers is beyond time windows.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Numerous variants of CVRP have been put forward and extensively studied which capture the complications of real-world problems [2][3][4], for example, VRP with time windows (VRPTW) [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21], in which customers have to be visited within a predefined time interval which can be described by the earliest arrival time and the latest arrival; VRP with multiple depots (VRPMD) [20,[22][23][24][25]; VRP with simultaneous delivery and pickup (VRPSDP) [10,26], where customers require simultaneous pickup and delivery service; VRP with stochastic demands (VRPSD) [19,[27][28][29][30][31][32][33][34][35], which involves demands that are random variables with known distributions; VRP with split delivery, where the demand of a customer can be split and delivered by multiple vehicles [36]; and the heterogeneous fleet VRP with several vehicle types [37].…”

Section: Introductionmentioning

confidence: 99%

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A Heuristics-Based Parthenogenetic Algorithm for the VRP with Potential Demands and Time Windows

Shi

Li²,

Bai

et al. 2016

Scientific Programming

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We present the vehicle routing problem with potential demands and time windows (VRP-PDTW), which is a variation of the classical VRP. A homogenous fleet of vehicles originated in a central depot serves customers with soft time windows and deliveries from/to their locations, and split delivery is considered. Also, besides the initial demand in the order contract, the potential demand caused by conformity consuming behavior is also integrated and modeled in our problem. The objective of minimizing the cost traveled by the vehicles and penalized cost due to violating time windows is then constructed. We propose a heuristics-based parthenogenetic algorithm (HPGA) for successfully solving optimal solutions to the problem, in which heuristics is introduced to generate the initial solution. Computational experiments are reported for instances and the proposed algorithm is compared with genetic algorithm (GA) and heuristics-based genetic algorithm (HGA) from the literature. The comparison results show that our algorithm is quite competitive by considering the quality of solutions and computation time.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Heuristics-Based Parthenogenetic Algorithm for the VRP with Potential Demands and Time Windows

Shi

Li²,

Bai

et al. 2016

Scientific Programming

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“…Tais elementos caracterizam o problema de um depósito para vários veículos, podendo ser entendido como um Problema de Roteamento de Veículos (PRV) clássico, que possui o objetivo de encontrar um conjunto de rotas de entrega que partem de um único Centro de Distribuição (CD), e ao terminar as entregas nos pontos de demanda, retornam ao mesmo ponto de partida, minimizando o custo total (LAPORTE et al, 2000;LOCOMME et al, 2015;GOODSON, 2015).…”

Section: Introductionunclassified

Roteamento de veículos sob restrições de capacidade e janelas de tempo em pequenas empresas utilizando as heurísticas das economias e da varredura

Gonçalves

Herzog

2017

Rev.Cienc. Tecn.

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A expansão das operações comerciais por meio do surgimento de mercados potenciais e do crescimento da globalização, tem direcionado os tomadores de decisão a maior atenção sobre a gestão das cadeias de distribuição. Ao selecionar um sistema de transporte as empresas devem considerar o custo total de deslocamento, e não apenas o valor do frete, consequentemente, torna-se importante a diminuição dos custos, que pode ser alcançada com a otimização do planejamento de rotas. A complexidade que envolve os processos de distribuição de cargas, bem como o aumento do número de partes envolvidas, demandam soluções que auxiliem tomadas de decisão e, nesse contexto, estão inseridos os Problemas de Roteamento de Veículos, (PRV) que ao serem resolvidos, podem auxiliar na elaboração e determinação de rotas para uma frota, de veículos a partir de um depósito central ligado a um conjunto de clientes. Por conseguinte, os resultados do uso de heurísticas construtivas para resolução do PRV sob restrições de capacidade e janelas de tempo, mostraram-se adequados a realidade vivenciada pela pequena empresa, além de poder servir como ferramenta para elaboração de estratégias competitivas.

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“…In 1995, originated from the flocking behavior of birds, particle swarm optimization (PSO) [6] was proposed for complex optimization problems. In decades, the intelligent optimization algorithms have widely been applied in many areas, such as transportation [7], power [8], Communication [9], Manufacturing [10], and so on.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Method for Evaluation of Production Scheduling Performance

Xu¹,

Yang²,

Wang

2015

Advances in Intelligent Systems Research

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To predict the production scheduling performance in a shop floor, an intelligent method based on a modified league championship algorithm is proposed. The method overcomes the problems like premature, being stuck to local minima, etc. A new match schedule is introduced to enhance the competition capability for every single team. One scheme for updating the team member is presented to diversify the population. The application of the proposed method on the production scheduling showed that the novel approach could provide accurate prediction of scheduling performance indexes and is capable of being used in the real world shop floor.

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A priori policy evaluation and cyclic-order-based simulated annealing for the multi-compartment vehicle routing problem with stochastic demands

Cited by 35 publications

References 23 publications

A Heuristics-Based Parthenogenetic Algorithm for the VRP with Potential Demands and Time Windows

A Heuristics-Based Parthenogenetic Algorithm for the VRP with Potential Demands and Time Windows

Roteamento de veículos sob restrições de capacidade e janelas de tempo em pequenas empresas utilizando as heurísticas das economias e da varredura

An Intelligent Method for Evaluation of Production Scheduling Performance

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