A genetic and set partitioning two-phase approach for the vehicle routing problem with time windows

Alvarenga, Guilherme Bastos; Mateus, Geraldo Robson; Tomi, Giorgio de

doi:10.1016/j.cor.2005.07.025

Cited by 204 publications

(91 citation statements)

References 16 publications

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“…Let a ir be a binary coefficient equal to 1 if and only if vertex i  V\{0} be Authors [31] suggest a genetic and set partitioning two-phase approach for the VRPTW. The VRPTW is formulated as a set partitioning p sed on natural reproduction, selection and evolution of Darwin's theory.…”

Section: Algorithms Based On the Set Partitioning Formulationmentioning

confidence: 99%

A Survey on the Vehicle Routing Problem and Its Variants

Kumar¹,

Panneerselvam²

2012

IIM

242

126

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In this paper, we have conducted a literature review on the recent developments and publications involving the vehicle routing problem and its variants, namely vehicle routing problem with time windows (VRPTW) and the capacitated vehicle routing problem (CVRP) and also their variants. The VRP is classified as an NP-hard problem. Hence, the use of exact optimization methods may be difficult to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large. The vehicle routing problem comes under combinatorial problem. Hence, to get solutions in determining routes which are realistic and very close to the optimal solution, we use heuristics and meta-heuristics. In this paper we discuss the various exact methods and the heuristics and meta-heuristics used to solve the VRP and its variants.

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Section: Algorithms Based On the Set Partitioning Formulationmentioning

confidence: 99%

A Survey on the Vehicle Routing Problem and Its Variants

Kumar¹,

Panneerselvam²

2012

IIM

242

126

View full text Add to dashboard Cite

show abstract

“…Repoussis et al [10] proposed a novel arc-guided evolution algorithm; there were parallel structures to solve the VRPTW. Alvarenga et al [11] combined the genetic algorithm (GA) with a set partition formulation; Malmborg [12] proposed a specific crossover operator based on graph theory for the VRPTW. The ant colony (ACO) has been applied to solve capacitated vehicle routing problems successfully [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Vehicle Routing Problem with Time Windows Using Multi-Objective Co-Evolutionary Approach

Wu¹,

Dong²,

Li³

2016

Int. j. simul. model.

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This paper introduces a novel multi-objective algorithm (HMPSO) based on discrete particle swarm optimization (PSO) to solve vehicle routing problems with time windows (VRPTW). The presented HMPSO algorithm was combined with an advanced discrete PSO based on set and variable neighbourhood searches to find Pareto optimal routing solutions. These consisted of a complete routing schedule for serving the customers to minimize the two aims of travelling distance and number of vehicles. To increase the discrete PSO efficiency, a novel decoding scheme based on set was designed, and the variable neighbourhood local search was employed to explore new solutions. The experiment results were showed for a set of the Solomon's 56 VRPTW. The HMPSO algorithm was compared with some algorithms published in papers with the computational evaluations clearly supporting the high performance of the proposed HMPSO algorithm against other algorithms, and confirming that the HMPSO is an efficient algorithm because of a reasonable computational time and cost in solve VRPTW.

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“…The travelled distance related to people and goods is very significant. It is motivated by the continuously increasing business complexity experienced today [1]. Based on King and Mast [2], 10 to 15 percent of the final values of traded goods correspond to its distance travel.…”

Section: Introductionmentioning

confidence: 99%

An Alternative Algorithm for Vehicle Routing Problem with Time Windows for Daily Deliveries

Ghani¹,

Shariff²,

Zahari³

2016

APM

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This study attempts to solve vehicle routing problem with time window (VRPTW). The study first identifies the real problems and suggests some recommendations on the issues. The technique used in this study is Genetic Algorithm (GA) and initialization applied is random population method. The objective of the study is to assign a number of vehicles to routes that connect customers and depot such that the overall distance travelled is minimized and the delivery operations are completed within the time windows requested by the customers. The analysis reveals that the problems experienced in vehicle routing with time window can be solved by GA and retrieved for optimal solutions. After a thorough study on VRPTW, it is highly recommended that a company should implement the optimal routes derived from the study to increase the efficiency and accuracy of delivery with time insertion.

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A genetic and set partitioning two-phase approach for the vehicle routing problem with time windows

Cited by 204 publications

References 16 publications

A Survey on the Vehicle Routing Problem and Its Variants

A Survey on the Vehicle Routing Problem and Its Variants

Vehicle Routing Problem with Time Windows Using Multi-Objective Co-Evolutionary Approach

An Alternative Algorithm for Vehicle Routing Problem with Time Windows for Daily Deliveries

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