Name
Abstract | ||
|---|---|---|
Knapsack problem is a classical combinatorial optimisation problem. This paper presents greedy continuous particle swarm optimisation (GCPSO) algorithm to solve the knapsack problem. First, the greedy strategy is introduced into the process of particles' initialisation based on standard particle swarm optimisation (SPSO). This strategy guarantees the particle swarm has a better beginning in a degree. Second, based on the analysis of the characteristics of the knapsack problem's solution space, and in terms of the binary code in evolutionary computation, the paper presents multi-state coding. To some extent, the multi-state coding reduces the data redundancy when encoding the solution of the knapsack problem. In experiments, the authors used discrete particle swarm algorithm as well as continuous particle swarm algorithm to find solutions for the knapsack problem. The experimental results show that the GCPSO algorithm provides better solution for the knapsack problems. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1504/IJCAT.2012.048684 | IJCAT |
Keywords | Field | DocType |
standard particle swarm optimisation,knapsack problem,optimisation algorithm,particle swarm,discrete particle swarm algorithm,gcpso algorithm,continuous particle swarm algorithm,multi-state coding,better solution,greedy continuous particle swarm,classical combinatorial optimisation problem,data redundancy | Particle swarm optimization,Mathematical optimization,Binary code,Generalized assignment problem,Algorithm,Evolutionary computation,Continuous knapsack problem,Data redundancy,Cutting stock problem,Knapsack problem,Mathematics | Journal |
Volume | Issue | ISSN |
44 | 2 | 0952-8091 |
Citations | PageRank | References |
2 | 0.38 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xianjun Shen | 1 | 24 | 12.95 |
| Yanan Li | 2 | 2 | 1.06 |
| Caixia Chen | 3 | 3 | 1.09 |
| Jincai Yang | 4 | 14 | 4.72 |
| Dabin Zhang | 5 | 3 | 1.45 |