Search Heuristic

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Gilbert Laporte - One of the best experts on this subject based on the ideXlab platform.

Michel Gendreau - One of the best experts on this subject based on the ideXlab platform.

  • a tabu Search Heuristic for the vehicle routing problem with two dimensional loading constraints
    Networks, 2008
    Co-Authors: Michel Gendreau, Gilbert Laporte, Manuel Iori, Silvaro Martello
    Abstract:

    This article addresses the well-known Capacitated Vehicle Routing Problem (CVRP), in the special case where the demand of a customer consists of a certain number of two-dimensional weighted items. The problem calls for the minimization of the cost of transportation needed for the delivery of the goods demanded by the customers, and carried out by a fleet of vehicles based at a central depot. In order to accommodate all items on the vehicles, a feasibility check of the two-dimensional packing (2L) must be executed on each vehicle. The overall problem, denoted as 2L-CVRP, is NP-hard and particularly difficult to solve in practice. We propose a Tabu Search algorithm, in which the loading component of the problem is solved through Heuristics, lower bounds, and a truncated branch-and-bound procedure. The effectiveness of the algorithm is demonstrated through extensive computational experiments. © 2007 Wiley Periodicals, Inc. NETWORKS, 2008

  • an efficient variable neighborhood Search Heuristic for very large scale vehicle routing problems
    Computers & Operations Research, 2007
    Co-Authors: Jari Kytojoki, Teemu Nuortio, Olli Braysy, Michel Gendreau
    Abstract:

    In this paper, we present an efficient variable neighborhood Search Heuristic for the capacitated vehicle routing problem. The objective is to design least cost routes for a fleet of identically capacitated vehicles to service geographically scattered customers with known demands. The variable neighborhood Search procedure is used to guide a set of standard improvement Heuristics. In addition, a strategy reminiscent of the guided local Search metaHeuristic is used to help escape local minima. The developed solution method is specifically aimed at solving very large scale real-life vehicle routing problems. To speed up the method and cut down memory usage, new implementation concepts are used. Computational experiments on 32 existing large scale benchmarks, as well as on 20 new very large scale problem instances, demonstrate that the proposed method is fast, competitive and able to find high-quality solutions for problem instances with up to 20,000 customers within reasonable CPU times.

  • availability optimization of series parallel multi state systems using a tabu Search meta Heuristic
    International Conference on Service Systems and Service Management, 2006
    Co-Authors: Mohamed Ouzineb, Mustapha Nourelfath, Michel Gendreau
    Abstract:

    This paper uses a new tabu Search meta-Heuristic optimization method to solve the redundancy allocation problem for multi-state series-parallel systems. The total Search space is divided into a set of disjoint subsets. The proposed tabu Search Heuristic determines the minimal cost system configuration under availability constraints. A universal generating function technique is applied to evaluate system availability. The algorithm was implemented and illustrated through numerical examples.

  • a dynamic model and parallel tabu Search Heuristic for real time ambulance relocation
    Parallel Computing, 2001
    Co-Authors: Michel Gendreau, Gilbert Laporte, Frédéric Semet
    Abstract:

    Abstract This paper considers the redeployment problem for a fleet of ambulances. This problem is encountered in the real-time management of emergency medical services. A dynamic model is proposed and a dynamic ambulance management system is described. This system includes a parallel tabu Search Heuristic to precompute redeployment scenarios. Simulations based on real-data confirm the efficiency of the proposed approach.

  • a tabu Search Heuristic for the heterogenous fleet vehicle routing problem
    Computers & Operations Research, 1999
    Co-Authors: Michel Gendreau, Gilbert Laporte, Eric D Taillard, Christophe Musaraganyi
    Abstract:

    Abstract The Heterogeneous Fleet Vehicle Routing Problem (HVRP) is a variant of the classical Vehicle Routing Problem in which customers are served by a heterogeneous fleet of vehicles with various capacities, fixed costs, and variable costs. This article describes a tabu Search Heuristic for the HVRP. On a set of benchmark instances, it consistently produces high-quality solutions, including several new best-known solutions. Scope and purpose In distribution management, it is often necessary to determine a combination of least cost vehicle routes through a set of geographically scattered customers, subject to side constraints. The case most frequently studied is where all vehicles are identical. This article proposes a solution methodology for the case where the vehicle fleet is heterogeneous. It describes an efficient tabu Search Heuristic capable of producing high-quality solutions on a series of benchmark test problems.

Jean François Cordeau - One of the best experts on this subject based on the ideXlab platform.

  • an adaptive large neighborhood Search Heuristic for two echelon vehicle routing problems arising in city logistics
    Computers & Operations Research, 2012
    Co-Authors: Vera C Hemmelmayr, Jean François Cordeau, Teodor Gabriel Crainic
    Abstract:

    In this paper, we propose an adaptive large neighborhood Search Heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP). The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood Search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm outperforms existing solution methods for the 2E-VRP and achieves excellent results on the LRP.

  • a parallel iterated tabu Search Heuristic for vehicle routing problems
    Computers & Operations Research, 2012
    Co-Authors: Jean François Cordeau, Mirko Maischberger
    Abstract:

    This paper introduces a parallel iterated tabu Search Heuristic for solving four different routing problems: the classical vehicle routing problem (VRP), the periodic VRP, the multi-depot VRP, and the site-dependent VRP. In addition, it is applicable to the time-window constrained variant of these problems. Using the iterated local Search framework, the Heuristic combines tabu Search with a simple perturbation mechanism to ensure a broad exploration of the Search space. We also describe a parallel implementation of the Heuristic to take advantage of multiple-core processors. Extensive computational results show that the proposed Heuristic outperforms tabu Search alone and is competitive with recent Heuristics designed for each particular problem.

  • A Hybrid Tabu Search and Constraint Programming Algorithm for the Dynamic Dial-a-Ride Problem
    INFORMS Journal on Computing, 2012
    Co-Authors: Gerardo Berbeglia, Jean François Cordeau, Gilbert Laporte
    Abstract:

    This paper introduces a hybrid algorithm for the dynamic dial-a-ride problem in which service requests arrive in real time. The hybrid algorithm combines an exact constraint programming algorithm and a tabu Search Heuristic. An important component of the tabu Search Heuristic consists of three scheduling procedures that are executed sequentially. Experiments show that the constraint programming algorithm is sometimes able to accept or reject incoming requests, and that the hybrid method outperforms each of the two algorithms when they are executed alone.

  • A large neighbourhood Search Heuristic for the aircraft and passenger recovery problem
    4OR, 2011
    Co-Authors: Serge Bisaillon, Gilbert Laporte, Jean François Cordeau, Federico Pasin
    Abstract:

    This paper introduces a large neighbourhood Search Heuristic for an airline recovery problem combining fleet assignment, aircraft routing and passenger assignment. Given an initial schedule, a list of disruptions, and a recovery period, the problem consists in constructing aircraft routes and passenger itineraries for the recovery period that allow the resumption of regular operations and minimize operating costs and impacts on passengers. The Heuristic alternates between construction, repair and improvement phases, which iteratively destroy and repair parts of the solution. The aim of the first two phases is to produce an initial solution that satisfies a set of operational and functional constraints. The third phase then attempts to identify an improved solution by considering large schedule changes while retaining feasibility. The whole process is iterated by including some randomness in the construction phase so as to diversify the Search. This work was initiated in the context of the 2009 ROADEF Challenge, a competition organized jointly by the French Operational ReSearch and Decision Analysis Society and the Spanish firm Amadeus S.A.S., in which our team won the first prize.

  • Scheduling technicians and tasks in a telecommunications company
    Journal of Scheduling, 2010
    Co-Authors: Jean François Cordeau, Federico Pasin, Gilbert Laporte, Stefan Ropke
    Abstract:

    This paper proposes a construction Heuristic and an adaptive large neighborhood Search Heuristic for the technician and task scheduling problem arising in a large telecommunications company. This problem was solved within the framework of the 2007 challenge set up by the French Operational ReSearch Society (ROADEF). The paper describes the authors’ entry in the competition which tied for second place.

Eric D Taillard - One of the best experts on this subject based on the ideXlab platform.

  • a tabu Search Heuristic for the heterogenous fleet vehicle routing problem
    Computers & Operations Research, 1999
    Co-Authors: Michel Gendreau, Gilbert Laporte, Eric D Taillard, Christophe Musaraganyi
    Abstract:

    Abstract The Heterogeneous Fleet Vehicle Routing Problem (HVRP) is a variant of the classical Vehicle Routing Problem in which customers are served by a heterogeneous fleet of vehicles with various capacities, fixed costs, and variable costs. This article describes a tabu Search Heuristic for the HVRP. On a set of benchmark instances, it consistently produces high-quality solutions, including several new best-known solutions. Scope and purpose In distribution management, it is often necessary to determine a combination of least cost vehicle routes through a set of geographically scattered customers, subject to side constraints. The case most frequently studied is where all vehicles are identical. This article proposes a solution methodology for the case where the vehicle fleet is heterogeneous. It describes an efficient tabu Search Heuristic capable of producing high-quality solutions on a series of benchmark test problems.

  • a tabu Search Heuristic for the vehicle routing problem with soft time windows
    Transportation Science, 1997
    Co-Authors: Eric D Taillard, Michel Gendreau, Philippe Badeau, Francois Guertin, Jeanyves Potvin
    Abstract:

    This paper describes a tabu Search Heuristic for the vehicle routing problem with soft time windows. In this problem, lateness at customer locations is allowed although a penalty is incurred and added to the objective value. By adding large penalty values, the vehicle routing problem with hard time windows can be addressed as well. In the tabu Search, a neighborhood of the current solution is created through an exchange procedure that swaps sequences of consecutive customers (or segments) between two routes. The tabu Search also exploits an adaptive memory that contains the routes of the best previously visited solutions. New starting points for the tabu Search are produced through a combination of routes taken from different solutions found in this memory. Many best-known solutions are reported on classical test problems.

  • a parallel tabu Search Heuristic for the vehicle routing problem with time windows
    Transportation Research Part C-emerging Technologies, 1997
    Co-Authors: Philippe Badeau, Jean-yves Potvin, Michel Gendreau, Francois Guertin, Eric D Taillard
    Abstract:

    The vehicle routing problem with time windows models many realistic applications in the context of distribution systems. In this paper, a parallel tabu Search Heuristic for solving this problem is developed and implemented on a network of workstations. Empirically, it is shown that parallelization of the original sequential algorithm does not reduce solution quality, for the same amount of computations, while providing substantial speed-ups in practice. Such speed-ups could be exploited to quickly produce high quality solutions when the time available for computing a solution is reduced, or to increase service quality by allowing the acceptance of new requests much later, as in transportation on demand systems.

Jean-yves Potvin - One of the best experts on this subject based on the ideXlab platform.

  • A tabu Search Heuristic for the vehicle routing problem with private fleet and common carrier
    European Journal of Operational Research, 2009
    Co-Authors: Jean-françois Côté, Jean-yves Potvin
    Abstract:

    This paper describes a tabu Search Heuristic for a vehicle routing problem where the owner of a private fleet can either visit a customer with one of his vehicles or assign the customer to a common carrier. The owner's objective is to minimize the variable and fixed costs for operating his fleet plus the total costs charged by the common carrier. The proposed tabu Search is shown to outperform the best approach reported in the literature on 34 benchmark instances with a homogeneous fleet.

  • a parallel tabu Search Heuristic for the vehicle routing problem with time windows
    Transportation Research Part C-emerging Technologies, 1997
    Co-Authors: Philippe Badeau, Jean-yves Potvin, Michel Gendreau, Francois Guertin, Eric D Taillard
    Abstract:

    The vehicle routing problem with time windows models many realistic applications in the context of distribution systems. In this paper, a parallel tabu Search Heuristic for solving this problem is developed and implemented on a network of workstations. Empirically, it is shown that parallelization of the original sequential algorithm does not reduce solution quality, for the same amount of computations, while providing substantial speed-ups in practice. Such speed-ups could be exploited to quickly produce high quality solutions when the time available for computing a solution is reduced, or to increase service quality by allowing the acceptance of new requests much later, as in transportation on demand systems.

  • the vehicle routing problem with time windows part i tabu Search
    Informs Journal on Computing, 1996
    Co-Authors: Jean-yves Potvin, Tanguy Kervahut, Brunolaurent Garcia, Jeanmarc Rousseau
    Abstract:

    This paper describes a tabu Search Heuristic for the vehicle routing problem with time windows. The tabu Search is based on specialized local Search Heuristics that maintain the feasibility of the solution at all time. Computational results on a standard set of test problems are reported, as well as comparisons with other Heuristics.