Name
Title | ||
|---|---|---|
Heuristic Generation of the Initial Population in Solving Job Shop Problems by Evolutionary Strategies |
Abstract | ||
|---|---|---|
In this work we confront the job shop scheduling problem by means of Genetic Algorithms. Our contribution is mainly the generation
of a heuristic initial population from domain specific knowledge provided by a probabilitic method. Experimental results show
that a Genetic Algorithm that uses a heuristic initial population outperforms not only the same algorithm when using a random
initial population, but also other search strategies that exploit the same class of heuristic information.
|
Year | DOI | Venue |
|---|---|---|
1999 | 10.1007/BFb0098227 | IWANN (1) |
Keywords | Field | DocType |
heuristic generation,initial population,evolutionary strategies,job shop problems,genetic algorithm,evolutionary strategy | Population,Incremental heuristic search,Mathematical optimization,Heuristic,Computer science,Job shop,Flow shop scheduling,Artificial intelligence,Local search (optimization),Null-move heuristic,Machine learning,Genetic algorithm | Conference |
Volume | ISSN | ISBN |
1606 | 0302-9743 | 3-540-66069-0 |
Citations | PageRank | References |
3 | 0.61 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ramiro Varela | 1 | 301 | 29.96 |
| Alberto Gomez | 2 | 50 | 12.62 |
| Camino R. Vela | 3 | 346 | 31.00 |
| Jorge Puente | 4 | 9 | 2.89 |
| Cesar Alonso | 5 | 60 | 8.45 |