|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|4959443||1445945||2018||15 صفحه PDF||سفارش دهید||دانلود کنید|
- We propose a novel cooperative swarm intelligence algorithm.
- It combines a firefly algorithm and a particle swarm optimization.
- It has been proposed to solve discrete multi-objective optimization problems.
- It has been applied to solve multi-objective knapsack.
- The obtained results show that our algorithm provides high convergence and coverage.
We propose a novel cooperative swarm intelligence algorithm to solve multi-objective discrete optimization problems (MODP). Our algorithm combines a firefly algorithm (FA) and a particle swarm optimization (PSO). Basically, we address three main points: the effect of FA and PSO cooperation on the exploration of the search space, the discretization of the two algorithms using a transfer function, and finally, the use of the epsilon dominance relation to manage the size of the external archive and to guarantee the convergence and the diversity of Pareto optimal solutions.We compared the results of our algorithm with the results of five well-known meta-heuristics on nine multi-objective knapsack problem benchmarks. The experiments show clearly the ability of our algorithm to provide a better spread of solutions with a better convergence behavior.
Journal: European Journal of Operational Research - Volume 264, Issue 1, 1 January 2018, Pages 74-88