A hybrid heuristic approach to minimize number of tardy jobs in group technology systems

Given a graph with its vertex set partitioned into a set of groups, nonnegative costs associated to its edges, and nonnegative prizes associated to its vertices, the prize‐collecting generalized minimum spanning tree problem consists in finding a subtree of this graph that spans exactly one vertex of each group and minimizes the sum of the costs of the edges of the tree less the prizes of the selected vertices. It is a generalization of the NP‐hard generalized minimum spanning tree optimization problem. We propose a GRASP (greedy randomized adaptive search procedure) heuristic for its approximate solution, incorporating path‐relinking for search intensification and a restart strategy for search diversification. The hybridization of the GRASP with path‐relinking and restarts heuristic with a data mining strategy that is applied along with the GRASP iterations, after the elite set is modified and becomes stable, contributes to making the heuristic more robust. The computational experiments show that the heuristic developed in this work found very good solutions for test problems with up to 439 vertices. All input data for the test instances and detailed numerical results are made available from Mendeley Data.

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“…Recent applications of GRASP are reported, for example, in Bajwa et al. (), Climaco et al. (), and Interian and Ribeiro ().…”

Section: Grasp Heuristic For Pc‐gmstpmentioning

confidence: 99%

A GRASP with path‐relinking and restarts heuristic for the prize‐collecting generalized minimum spanning tree problem

Marzo

Ribeiro

2019

Int Trans Operational Res

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“…A hybrid parameter tuning approach has been proposed to optimize performance metrics of these algorithms [12]. Bajwa et al [13] and Cao et al [14] explored scheduling in group technology systems and production workshops, respectively, using these optimized algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

Enhancing Evolutionary Solver Efficiency for NP-Hard Single Machine Scheduling Problems

Al-Romema,

A. Makarem

2023

IJSR

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The study explores the optimization of evolutionary solver parameters for minimizing total tardiness in single machine scheduling, an NP-hard problem with zero ready times included. It investigates various parameter combinations, including population sizes, mutation rates, and a constant convergence rate, both above and below default values. The aim is to enhance the solver's effectiveness in addressing this complex challenge. The findings contribute to improving scheduling efficiency in manufacturing and operations management contexts.

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“…The GRASP was adopted to enhance search efficiency, and the resulting suitable solutions were further employed as particles by the PSO algorithm to achieve local and global solutions. This hybrid heuristic was proved to be effective for 63% of problem instances [30]. In order to solve vehicle routing problems with time windows, Marinakis et al presented a new variant of PSO based on three strategies: GRASP for solution initialization, adaptive combinatorial neighborhood topology for particles movement, and adaptive calculation of parameters.…”

Section: Literature Reviewmentioning

confidence: 99%

Greedy Mechanism Based Particle Swarm Optimization for Path Planning Problem of an Unmanned Surface Vehicle

Xin

Zhong

et al. 2019

Sensors

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Recently, issues of climate change, environment abnormality, individual requirements, and national defense have caused extensive attention to the commercial, scientific, and military development of unmanned surface vehicles (USVs). In order to design high-quality routes for a multi-sensor integrated USV, this work improves the conventional particle swarm optimization algorithm by introducing the greedy mechanism and the 2-opt operation, based on a combination strategy. First, a greedy black box is established for particle initialization, overcoming the randomness of the conventional method and excluding a great number of infeasible solutions. Then the greedy selection strategy and 2-opt operation are adopted together for local searches, to maintain population diversity and eliminate path crossovers. In addition, Monte-Carlo simulations of eight instances are conducted to compare the improved algorithm with other existing algorithms. The computation results indicate that the improved algorithm has the superior performance, with the shortest route and satisfactory robustness, although a fraction of computing efficiency becomes sacrificed. Moreover, the effectiveness and reliability of the improved method is also verified by its multi-sensor-based application to a USV model in real marine environments.

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A hybrid heuristic approach to minimize number of tardy jobs in group technology systems

Cited by 10 publications

References 50 publications

A GRASP with path‐relinking and restarts heuristic for the prize‐collecting generalized minimum spanning tree problem

A GRASP with path‐relinking and restarts heuristic for the prize‐collecting generalized minimum spanning tree problem

Enhancing Evolutionary Solver Efficiency for NP-Hard Single Machine Scheduling Problems

Greedy Mechanism Based Particle Swarm Optimization for Path Planning Problem of an Unmanned Surface Vehicle

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