Local search heuristics for single machine tardiness sequencing
Author: Crauwels, H. A. J ; Potts, C. N. ; Van Wassenhove, Luk N.INSEAD Area: Technology and Operations Management Series: Working Paper ; 94/52/TM Publisher: Fontainebleau : INSEAD, 1994.Language: EnglishDescription: 15 p.Type of document: INSEAD Working Paper Online Access: Click here Abstract: This paper presents several local search heuristics for the problem of scheduling a single machine to minimize total weighted tardiness. A genetic algorithm is developed which employs a new binary encoding scheme to represent solutions and uses a heuristic method to convert the representation into a sequence. This algorithm is compared to descent, simulated annealing and tabu search methods on a large set of test problems. The computational results indicate that tabu search performs better than the order two neighbourhood search methods. However, the genetic algorithm generally produces superior solutions and it also appears to be a robust heuristic| Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Digital Library | Available | BC001042 |
This paper presents several local search heuristics for the problem of scheduling a single machine to minimize total weighted tardiness. A genetic algorithm is developed which employs a new binary encoding scheme to represent solutions and uses a heuristic method to convert the representation into a sequence. This algorithm is compared to descent, simulated annealing and tabu search methods on a large set of test problems. The computational results indicate that tabu search performs better than the order two neighbourhood search methods. However, the genetic algorithm generally produces superior solutions and it also appears to be a robust heuristic
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