The mixed capacitated general routing problem under uncertainty

•Probabilistically constrained formulation.•Deterministic formulation where uncertain parameters follow a normal distribution.•Branch-and-cut algorithm and an efficient heuristic algorithm. We study the General Routing Problem defined on a mixed graph and with stochastic demands. The problem under i...

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Vydané v:European journal of operational research Ročník 240; číslo 2; s. 382 - 392
Hlavní autori: Beraldi, Patrizia, Bruni, Maria Elena, Laganà, Demetrio, Musmanno, Roberto
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Elsevier B.V 16.01.2015
Elsevier Sequoia S.A
Predmet:
Branch & bound algorithms
Effectiveness studies
Heuristic
Integer programming
Mixed graph
Neighborhood search
Probabilistic constraints
Route optimization
Routing problem
Stochastic models
Transportation problem (Operations research)
Neighborhood search
Probabilistic constraints
Mixed graph
Routing problem
ISSN:0377-2217, 1872-6860
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Popis
Shrnutí:•Probabilistically constrained formulation.•Deterministic formulation where uncertain parameters follow a normal distribution.•Branch-and-cut algorithm and an efficient heuristic algorithm. We study the General Routing Problem defined on a mixed graph and with stochastic demands. The problem under investigation is aimed at finding the minimum cost set of routes to satisfy a set of clients whose demand is not deterministically known. Since each vehicle has a limited capacity, the demand uncertainty occurring at some clients affects the satisfaction of the capacity constraints, that, hence, become stochastic. The contribution of this paper is twofold: firstly we present a chance-constrained integer programming formulation of the problem for which a deterministic equivalent is derived. The introduction of uncertainty into the problem poses severe computational challenges addressed by the design of a branch-and-cut algorithm, for the exact solution of limited size instances, and of a heuristic solution approach exploring promising parts of the search space. The effectiveness of the solution approaches is shown on a probabilistically constrained version of the benchmark instances proposed in the literature for the mixed capacitated general routing problem.
Bibliografia:SourceType-Scholarly Journals-1
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content type line 14
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2014.07.023