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2018•Computación y SistemasRequires access

Effect of Parameters Tuned by a Taguchi Design L_9 3^4 in the GRASP Algorithm to Solve the Vehicle Routing Problem with Time Windows

Alma Danisa Romero Ocaño, María de los Ángeles Cosío-León, Víctor Manuel Valenzuela Alcaraz, Gener Avilés-Rodríguez, Anabel Martínez-Vargas

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Abstract

Metaheuristic algorithms are black box procedures that analyze a subset of possible solutions to solve a problem or a set of instances. Before they are implemented, it is necessary to select an optimum parameter vector P ∗, a task known as tuning. The vector P ∗ affects the efficiency of metaheuristics in solving a given problem. In this paper, the impact of tuning parameters using the Taguchi L_9 3^4 statistical procedure is analyzed. The effect of this method is analyzed in the metaheuristic algorithm named Greedy Randomized Adaptive Search Procedure (GRASP), solving the problem of Vehicle Routes with Time Windows (VRPTW). The results offered by the algorithm in a subset of instances of 25 clients improve on average to those reported in the literature, using a P ∗ proposed by Taguchi calibration.

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What this paper is about

Metaheuristic algorithms are black box procedures that analyze a subset of possible solutions to solve a problem or a set of instances. Before they are implemented, it is necessary to select an optimum parameter vector P ∗, a task known as tuning. The vector P ∗ affects the efficiency of metaheuristics in solving a given problem. In this paper, the impact of tuning parameters using the Taguchi L_9 3^4 statistical procedure is analyzed. The effect of this method is analyzed in the metaheuristic algorithm named Greedy Randomized Adaptive Search Procedure (GRASP), solving the problem of Vehicle Routes with Time Windows (VRPTW). The results offered by the algorithm in a subset of instances of 25 clients improve on average to those reported in the literature, using a P ∗ proposed by Taguchi calibration.

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Available abstract

Metaheuristic algorithms are black box procedures that analyze a subset of possible solutions to solve a problem or a set of instances. Before they are implemented, it is necessary to select an optimum parameter vector P ∗, a task known as tuning. The vector P ∗ affects the efficiency of metaheuristics in solving a given problem. In this paper, the impact of tuning parameters using the Taguchi L_9 3^4 statistical procedure is analyzed. The effect of this method is analyzed in the metaheuristic algorithm named Greedy Randomized Adaptive Search Procedure (GRASP), solving the problem of Vehicle Routes with Time Windows (VRPTW). The results offered by the algorithm in a subset of instances of 25 clients improve on average to those reported in the literature, using a P ∗ proposed by Taguchi calibration.

Key concepts: Taguchi methods, GRASP, Metaheuristic, Greedy randomized adaptive search procedure, Vehicle routing problem, Mathematical optimization, Set (abstract data type), Algorithm

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Effect of Parameters Tuned by a Taguchi Design L_9 3^4 in the GRASP Algorithm to Solve the Vehicle Routing Problem with Time Windows — Research Paper | ScholarLens