Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem

Osman, Ibrahim H.

doi:10.1007/bf02023004

Cited by 843 publications

(355 citation statements)

References 30 publications

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“…In this section we will present numerical results for our new approach(HRACS) and compare them with results from previous Ant Colony System algorithm(ACS) [11] for the VRP as well as TABUROUTE algorithm(TS) [20] and Simulated Annealing algorithm(SA) [21]. The numerical analysis was performed on a set of benchmark problems described in [22].…”

Section: Numerical Resultsmentioning

confidence: 99%

A Modified Ant Algorithm for Solving the Vehicle Routing Problem

Qi¹

2007

Proceedings on Intelligent Systems and Knowledge Engineering (ISKE2007)

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The ant system is a metaheuristic developed for the solution of hard combinatorial optimization problems. In this paper, through an analysis of the constructive procedure of the solution in the Ant Colony System (ACS), a modified algorithm for solving Vehicle Routing Problem (VRP), based on the ACS Hybridized with Randomized Algorithm(HRACS), is proposed. In HRACS, only partial customers are randomly chosen to compute the transition probability. Experiments on various aspects of the algorithm and computational results for fourteen benchmark problems are reported. We compare our approach with some other meta-heuristics and show that our results are competitive.

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Section: Numerical Resultsmentioning

confidence: 99%

A Modified Ant Algorithm for Solving the Vehicle Routing Problem

Qi¹

2007

Proceedings on Intelligent Systems and Knowledge Engineering (ISKE2007)

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“…Tabu search was first introduced for solving VRP by Willard [49]. Later on, different groups of researchers designed a variety of neighborhood/moves and adopted some problem-specific mechanism to significantly improve the performance, see for instance [39,20,50,47]. Tabu search has also been applied to major variants of VRP, e.g.…”

Section: Tabu Heuristic Solution Approachmentioning

confidence: 99%

The Stochastic Vehicle Routing Problem for Minimum Unmet Demand

Shen

Ordóñez

Dessouky

2009

Springer Optimization and Its Applications

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Summary. In this paper, we are interested in routing vehicles to minimize unmet demand with uncertain demand and travel time parameters. Such a problem arises in situations with large demand or tight deadlines, so that routes that satisfy all demand points are difficult or impossible to obtain. An important application is the distribution of medical supplies to respond to large-scale emergencies, such as natural disasters or terrorist attacks. We present a chance constrained formulation of the problem that is equivalent to a deterministic problem with modified demand and travel time parameters, under mild assumptions on the distribution of stochastic parameters; and relate it with a robust optimization approach. A tabu heuristic is proposed to solve this MIP and simulations are conducted to evaluate the quality of routes generated from both deterministic and chance constrained formulations. We observe that chance constrained routes can reduce the unmet demand by around 2%-6% for moderately tight deadline and total supply constraints.

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“…Pauses are often seen in long-haul transportation when drivers are required to stop and rest after a 20 given number of driving hours to avoid excessively long working shifts [4,11,12,13,14,15,31]. In last mile distribution, pauses are also present, for example, when drivers have time allotted for lunch breaks.…”

Section: Introductionmentioning

confidence: 99%

“…This strategy can be applied for problems in which the pause separates two delivery periods, similar to a multi-period problem [1]. 20 However, in a short planning horizon such as daily delivery in which our problem is defined, the pause does not lead to a multi-period problem. In fact, this strategy does not suit the retail industry where many customer deliveries should be done within some (tight) time windows and where service quality is highly important.…”

Section: Introductionmentioning

confidence: 99%

Solving the vehicle routing problem with lunch break arising in the furniture delivery industry

Coelho

Gagliardi

Ruiz

2016

Journal of the Operational Research Society

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5In this paper we solve the Vehicle Routing Problem with Lunch Break (VRPLB) which arises when drivers must take pauses during their shift, for example, for lunch breaks. Driver breaks have already been considered in long haul transportation when drivers must rest during their travel, but the underlying optimization problem remains difficult and few contributions can be found for These results demonstrate the importance of integrating drivers pauses in the resolution process.

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Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem

Cited by 843 publications

References 30 publications

A Modified Ant Algorithm for Solving the Vehicle Routing Problem

A Modified Ant Algorithm for Solving the Vehicle Routing Problem

The Stochastic Vehicle Routing Problem for Minimum Unmet Demand

Solving the vehicle routing problem with lunch break arising in the furniture delivery industry

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