A genetic algorithm for a single-machine bi-criterion scheduling problem with release times and learning consideration
| Autor: | Ming-Fang Liu, 劉明芳 |
|---|---|
| Jazyk: | zh-TW |
| Rok vydání: | 2008 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 96 The learning effect in scheduling field has received considerable attention recently. However, most researchers consider a single criterion with the assumption that all jobs are ready to be processed. The research of bi-criterion problems with learning effect is relatively limited. This paper studies a single-machine learning effect scheduling problem with release times where the objective is to minimize the combination of the makespan and total completion times. First, we develop a branch-and-bound algorithm incorporating with several dominance properties and a lower bound to derive the optimal solution. Secondly, we propose a genetic algorithm to obtain near-optimal solutions. Finally, a computational experiment is conducted to evaluate the performance of the branch-and-bound and the genetic algorithms. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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