An effective memetic algorithm for the cumulative capacitated vehicle routing problem

Ngueveu, Sandra Ulrich; Prins, Christian; Calvo, Roberto Wolfler

doi:10.1016/j.cor.2009.06.014

Cited by 190 publications

(147 citation statements)

References 17 publications

(32 reference statements)

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“…These creatures are not very intelligent individually whereas they show intelligent and complex behavior while working collectively; see, for example, the foraging behavior of bees for honey collection. Swarm-based metaheuristics are also getting remarkable attention from many researchers in dealing optimization problems like CVRP and its variations [31][32][33][34][35][36][37].…”

Section: Introductionmentioning

confidence: 99%

Bilayer Local Search Enhanced Particle Swarm Optimization for the Capacitated Vehicle Routing Problem

Ahmed

Sun

2018

Algorithms

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Abstract:The classical capacitated vehicle routing problem (CVRP) is a very popular combinatorial optimization problem in the field of logistics and supply chain management. Although CVRP has drawn interests of many researchers, no standard way has been established yet to obtain best known solutions for all the different problem sets. We propose an efficient algorithm Bilayer Local Search-based Particle Swarm Optimization (BLS-PSO) along with a novel decoding method to solve CVRP. Decoding method is important to relate the encoded particle position to a feasible CVRP solution. In bilayer local search, one layer of local search is for the whole population in any iteration whereas another one is applied only on the pool of the best particles generated in different generations. Such searching strategies help the BLS-PSO to perform better than the existing proposals by obtaining best known solutions for most of the existing benchmark problems within very reasonable computational time. Computational results also show that the performance achieved by the proposed algorithm outperforms other PSO-based approaches.

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Section: Introductionmentioning

confidence: 99%

Bilayer Local Search Enhanced Particle Swarm Optimization for the Capacitated Vehicle Routing Problem

Ahmed

Sun

2018

Algorithms

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“…Metaheuristics are problem-independent methodologies that provide a set of guidelines for heuristic optimization algorithms [18]. Among these, memetic algorithms are highly effective population-based metaheuristics which have been successfully applied to a range of combinatorial optimisation problems [2,8,10,11,14]. Memetic algorithms, introduced by Moscato [12], hybridise genetic algorithms with local search.…”

Section: Introductionmentioning

confidence: 99%

An Analysis of the Taguchi Method for Tuning a Memetic Algorithm with Reduced Computational Time Budget

Gumus

Özcan

Atkin

2016

Communications in Computer and Information Science

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Abstract. Determining the best initial parameter values for an algorithm, called parameter tuning, is crucial to obtaining better algorithm performance; however, it is often a time-consuming task and needs to be performed under a restricted computational budget. In this study, the results from our previous work on using the Taguchi method to tune the parameters of a memetic algorithm for cross-domain search are further analysed and extended. Although the Taguchi method reduces the time spent finding a good parameter value combination by running a smaller size of experiments on the training instances from different domains as opposed to evaluating all combinations, the time budget is still larger than desired. This work investigates the degree to which it is possible to predict the same good parameter setting faster by using a reduced time budget. The results in this paper show that it was possible to predict good combinations of parameter settings with a much reduced time budget. The good final parameter values are predicted for three of the parameters, while for the fourth parameter there is no clear best value, so one of three similarly performing values is identified at each time instant.

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“…They have been applied to a range of combinatorial optimisation problems, including educational timetabling [2], [21], parallel code optimisation [22], quadratic assignment [16], vehicle routing [18], the travelling salesman problem [13], protein structure prediction [12] and knapsack problems [10]. Parameter tuning, i.e.…”

Section: Introductionmentioning

confidence: 99%

An investigation of tuning a memetic algorithm for cross-domain search

Gumus

Özcan

Atkin

2016

2016 IEEE Congress on Evolutionary Computation (CEC)

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Abstract-Memetic algorithms, which hybridise evolutionary algorithms with local search, are well-known metaheuristics for solving combinatorial optimisation problems. A common issue with the application of a memetic algorithm is determining the best initial setting for the algorithmic parameters, but these can greatly influence its overall performance. Unlike traditional studies where parameters are tuned for a particular problem domain, in this study we do tuning that is applicable to cross-domain search. We extend previous work by tuning the parameters of a steady state memetic algorithm via a 'design of experiments' approach and provide surprising empirical results across nine problem domains, using a cross-domain heuristic search tool, namely HyFlex. The parameter tuning results show that tuning has value for cross-domain search. As a side gain, the results suggest that the crossover operators should not be used and, more interestingly, that single point based search should be preferred over a population based search, turning the overall approach into an iterated local search algorithm. The use of the improved parameter settings greatly enhanced the crossdomain performance of the algorithm, converting it from a poor performer in previous work to one of the stronger competitors.

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An effective memetic algorithm for the cumulative capacitated vehicle routing problem

Cited by 190 publications

References 17 publications

Bilayer Local Search Enhanced Particle Swarm Optimization for the Capacitated Vehicle Routing Problem

Bilayer Local Search Enhanced Particle Swarm Optimization for the Capacitated Vehicle Routing Problem

An Analysis of the Taguchi Method for Tuning a Memetic Algorithm with Reduced Computational Time Budget

An investigation of tuning a memetic algorithm for cross-domain search

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