This article presents an approach to integrate a Pareto dominance concept into a comprehensive learning particle swarm optimizer ~CLPSO! to handle multiple objective optimization problems. The multiobjective comprehensive learning particle swarm optimizer ~MOCLPSO! also integrates an external archiv
Solving shortest path problem using particle swarm optimization
โ Scribed by Ammar W. Mohemmed; Nirod Chandra Sahoo; Tan Kim Geok
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 950 KB
- Volume
- 8
- Category
- Article
- ISSN
- 1568-4946
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
This paper presents a co-evolutionary particle swarm optimization (CPSO) algorithm to solve global nonlinear optimization problems. A new co-evolutionary PSO (CPSO) is constructed. In the algorithm, a deterministic selection strategy is proposed to ensure the diversity of population. Meanwhile, base
Bi-level linear programming is a technique for modeling decentralized decision. It consists of the upper-level and lower-level objectives. This paper attempts to develop an efficient method based on particle swarm optimization (PSO) algorithm with swarm intelligence. The performance of the proposed
algorithm a b s t r a c t The multilevel lot-sizing (MLLS) problem is a key production planning problem in materials requirements planning (MRP) system. The MLLS problem deals with determining the production lot-sizes of various items appearing in the product structure over a given finite planning