Name
Title | ||
|---|---|---|
Agent-based simheuristics - Extending simulation-Optimization Algorithms via Distributed and Parallel Computing. |
Abstract | ||
|---|---|---|
This paper presents a novel agent-based simheuristic (ABSH) approach that combines simheuristic and multi-agent system to efficiently solve stochastic combinatorial optimization problems. In an ABSH approach, multiple agents cooperate in searching a near-optimal solution to a stochastic combinatorial optimization problem inside a vast space of feasible solutions. Each of these agents is a simheuristic algorithm integrating simulation within a metaheuristic optimization framework. Each agent follows a different pattern while exploring the solution space. However, all simheuristic agents cooperate in the search of a near-optimal solution by sharing critical information among them. The distributed nature of the multi-agent system makes it easy for ABSH to make use of parallel and distributed computing technology. This paper discusses the potential of this novel simulation-optimization approach and illustrates, with a computational experiment, the advantages that ABSH approaches offer over traditional simheuristic ones. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/WSC.2018.8632426 | WSC |
Keywords | Field | DocType |
Stochastic processes,Computational modeling,Optimization,Uncertainty,Space exploration,Analytical models,Routing | Systems engineering,Combinatorial optimization problem,Computer science,Metaheuristic optimization,Stochastic process,Space exploration,Optimization algorithm,Distributed computing | Conference |
ISSN | ISBN | Citations |
0891-7736 | 978-1-5386-6572-5 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Javier Panadero | 1 | 18 | 8.03 |
| Angel A. Juan | 2 | 596 | 69.73 |
| Jose M. Mozos | 3 | 0 | 0.34 |
| Canan G. Corlu | 4 | 30 | 6.12 |
| B S S Onggo | 5 | 82 | 14.17 |