GRASP-based heuristic algorithm for the multi-product multi-vehicle inventory routing problem

Oualid Guemri (), Abdelghani Bekrar (), Bouziane Beldjilali () and Damien Trentesaux ()
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Oualid Guemri: University of Oran 1 Ahmed BenBella
Abdelghani Bekrar: University of Valenciennes and Hainaut Cambresis
Bouziane Beldjilali: University of Oran 1 Ahmed BenBella
Damien Trentesaux: University of Valenciennes and Hainaut Cambresis

4OR, 2016, vol. 14, issue 4, No 3, 377-404

Abstract: Abstract In this paper, we introduce an improved Greedy Randomized Adaptive Search Procedure (GRASP) based heuristic for the multi-product multi-vehicle inventory routing problem (MMIRP). The inventory routing problem, which combines the vehicle-routing problem and the inventory control decisions, is one of the most important problems in combinatorial optimization field. To deal with the MMIRP, we develop a GRASP-based heuristic (GBH). Each GBH iteration consists of two sequential phases; the first phase is a Greedy Randomized Procedure, in which, the best tradeoff between the inventory holding cost and routing cost is looked. Then, in the second phase, as local search for the GRASP, we use the Tabu search (TS) meta-heuristic to improve the solution found in the first phase. The GBH two phases are repeated until some stopped criterion is met. Our proposed method is evaluated on two benchmark data sets, and successfully compared with two state-of-the-art algorithms.

Keywords: Optimization; Multi product multi vehicle inventory routing; Meta-heuristics; GRASP; Tabu search; 90C27; 90B06; 90B05; 90C59 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10288-016-0315-1

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