Cyclic-order neighborhoods with application to the vehicle routing problem with stochastic demand

Goodson, Justin; Ohlmann, Jeffrey W.; Thomas, Barrett W.

doi:10.1016/j.ejor.2011.09.023

Cited by 62 publications

(49 citation statements)

References 33 publications

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“…In this case, only one vehicle is used. Considering these issues, the proposed hybrid is tested for the benchmark in [4,16,34]. Note, however, that the obtained results are not be directly comparable to those of [4,16] due to different handling of route failure.…”

Section: Resultsmentioning

confidence: 99%

“…Considering these issues, the proposed hybrid is tested for the benchmark in [4,16,34]. Note, however, that the obtained results are not be directly comparable to those of [4,16] due to different handling of route failure. We use the same transformation of the customers demands as the one proposed by [4,16] and therefore we assume customer demands to be independent Poisson random variables with the mean demand for each customer equal to the deterministic value of the demand given in the corresponding VRP problem.…”

Section: Resultsmentioning

confidence: 99%

“…In Table 2, the results of the proposed hybrid algorithm for a set of forty benchmark instances [4,16] are presented. The first column of Table 2 gives the names of the instances, which, in turn, include the number of nodes and the number of vehicles.…”

Section: Resultsmentioning

confidence: 99%

“…Both approaches have as a goal the minimization of the expected cost. In one approach [4,16], vehicles follow their assigned routes until a route failure occurs. Then a replenishment is performed at the depot and subsequently the vehicle returns to the customer where the route failure occurred and resumes the servicing.…”

Section: Resultsmentioning

confidence: 99%

“…This means that the vehicle returns to the depot for replenishment in order to avoid the risk of visiting the next customer without having sufficient load. Concerning the solution of the VRPSD, a number of algorithms have been proposed in the literature [1,2,4,16,[21][22][23].…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Clonal Selection Algorithm for the Vehicle Routing Problem with Stochastic Demands

Marinakis

Marinaki

Migdalas

2014

Lecture Notes in Computer Science

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Abstract. The Clonal Selection Algorithm is the most known algorithm inspired from the Artificial Immune Systems and used effectively in optimization problems. In this paper, this nature inspired algorithm is used in a hybrid scheme with other metaheuristic algorithms for successfully solving the Vehicle Routing Problem with Stochastic Demands (VRPSD). More precisely, for the solution of this problem, the Hybrid Clonal Selection Algorithm (HCSA) is proposed which combines a Clonal Selection Algorithm (CSA), a Variable Neighborhood Search (VNS), and an Iterated Local Search (ILS) algorithm. The effectiveness of the original Clonal Selection Algorithm for this NP-hard problem is improved by using ILS as a hypermutation operator and VNS as a receptor editing operator. The algorithm is tested on a set of 40 benchmark instances from the literature and ten new best solutions are found. Comparisons of the proposed algorithm with several algorithms from the literature (two versions of the Particle Swarm Optimization algorithm, a Differential Evolution algorithm and a Genetic Algorithm) are also reported.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Hybrid Clonal Selection Algorithm for the Vehicle Routing Problem with Stochastic Demands

Marinakis

Marinaki

Migdalas

2014

Lecture Notes in Computer Science

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A Bi‐Objective Inventory Routing Problem for Sustainable Waste Management Under Uncertainty

Nolz

Absi

Feillet

2014

Multi Criteria Decision Anal

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The fast increase in waste materials disposed of by home-health and medical care services as well as by self-attending patients leads to a major concern over the safe disposal of health care waste. In this paper, we consider the design of a collection system for infectious medical waste. These waste materials are produced by patients in self-treatment, stored at pharmacies and picked up by local authorities for disposal.The stochastic waste collection problem is formulated considering two conflicting objective functions. Social objectives, specifically the satisfaction of pharmacists and local authorities involved in the collection process, as well as the minimization of public health risks need to be traded off against distribution costs comprising routing costs and fixed costs incurred each time a tour is planned. We propose three heuristic solution approaches to solve the real-world motivated inventory routing problem. The suggested methods are tested on real-world data from the region of Provence-Alpes-Côte d'Azur, in France, and their performance is evaluated with several quality indicators.

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A Recourse Stochastic Goal Programming Approach for the Multi-objective Stochastic Vehicle Routing Problem

Masri

Abdelaziz

Alaya

2016

J. Multi-Crit. Decis. Anal.

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This paper addresses a multi-objective stochastic vehicle routing problem where several conflicting objectives such as the travel time, the number of vehicles in use and the probability of an accident are simultaneously minimized. We suppose that demands and travel durations are of a stochastic nature. In order to build a certainty equivalent program to the multi-objective stochastic vehicle routing problem, we propose a solution strategy based on a recourse approach, a chance-constrained approach and a goal-programming approach. The resulting certainty equivalent program is solved to optimality using CPLEX.

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Cyclic-order neighborhoods with application to the vehicle routing problem with stochastic demand

Cited by 62 publications

References 33 publications

A Hybrid Clonal Selection Algorithm for the Vehicle Routing Problem with Stochastic Demands

A Hybrid Clonal Selection Algorithm for the Vehicle Routing Problem with Stochastic Demands

A Bi‐Objective Inventory Routing Problem for Sustainable Waste Management Under Uncertainty

A Recourse Stochastic Goal Programming Approach for the Multi-objective Stochastic Vehicle Routing Problem

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