Improving local search heuristics for some scheduling problems. Part II

Peter Brucker; Johann L. Hurink; Frank Werner

doi:10.1016/S0166-218X(96)00036-4

Improving local search heuristics for some scheduling problems. Part II

Peter Brucker, Johann L. Hurink, Frank Werner

Discrete Mathematics and Mathematical Programming

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Abstract

Local search techniques like simulated annealing and tabu search are based on a neighborhood structure defined on the set of feasible solutions of a discrete optimization problem. For the scheduling problems $Pm||C_{max}, 1|prec|\sum U_i,$ and a large class of sequencing problems with precedence constraints having local interchange properties we replace a simple neighborhood by a neighborhood on the set of all locally optimal solutions. This allows local search on the set of solutions that are locally optimal. Computational results are presented.

Original language	English
Pages (from-to)	47-69
Number of pages	23
Journal	Discrete applied mathematics
Volume	72
Issue number	1-2
DOIs	https://doi.org/10.1016/S0166-218X(96)00036-4
Publication status	Published - 10 Jan 1997

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title = "Improving local search heuristics for some scheduling problems. Part II",

abstract = "Local search techniques like simulated annealing and tabu search are based on a neighborhood structure defined on the set of feasible solutions of a discrete optimization problem. For the scheduling problems $Pm||C_{max}, 1|prec|\sum U_i,$ and a large class of sequencing problems with precedence constraints having local interchange properties we replace a simple neighborhood by a neighborhood on the set of all locally optimal solutions. This allows local search on the set of solutions that are locally optimal. Computational results are presented.",

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AB - Local search techniques like simulated annealing and tabu search are based on a neighborhood structure defined on the set of feasible solutions of a discrete optimization problem. For the scheduling problems $Pm||C_{max}, 1|prec|\sum U_i,$ and a large class of sequencing problems with precedence constraints having local interchange properties we replace a simple neighborhood by a neighborhood on the set of all locally optimal solutions. This allows local search on the set of solutions that are locally optimal. Computational results are presented.

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Improving local search heuristics for some scheduling problems. Part II

Abstract

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