EFFICIENT NEIGHBORHOOD SEARCH FOR THE PROBABILISTIC MULTI-VEHICLE PICKUP AND DELIVERY PROBLEM

Patrizia Beraldi (), Gianpaolo Ghiani (), Roberto Musmanno () and Francesca Vocaturo ()
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Patrizia Beraldi: Dipartimento di Elettronica, Informatica e Sistemistica, Università della Calabria, 87036 Arcavacata di Rende (CS), Italy
Gianpaolo Ghiani: Dipartimento di Ingegneria dell'Innovazione, Università del Salento, 73100 Lecce, Italy
Roberto Musmanno: Dipartimento di Elettronica, Informatica e Sistemistica, Università della Calabria, 87036 Arcavacata di Rende (CS), Italy
Francesca Vocaturo: Dipartimento di Economia e Statistica, Università della Calabria, 87036 Arcavacata di Rende (CS), Italy

Asia-Pacific Journal of Operational Research (APJOR), 2010, vol. 27, issue 03, 301-314

Abstract: This paper deals with the probabilistic multi-vehicle pickup and delivery problem. We develop an efficient neighborhood evaluation procedure which allows to reduce the computational complexity by two orders of magnitude with respect to a straightforward approach. The numerical experiments indicate that, if incorporated in a local search strategy, our neighborhood evaluation technique, provides very good results in terms of computation time reduction and equity of the workload distribution among the available vehicles.

Keywords: Stochastic vehicle routing; minmax objective function; local search (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (6)

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DOI: 10.1142/S0217595910002715

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