An Improved Binary Wolf Pack Algorithm Based on Adaptive Step Length and Improved Update Strategy for 0-1 Knapsack Problems

• 作者: Liting Guo Sanyang Liu
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: BINARY WOLF PACK ALGORITHM 0-1 knapsack problem ADAPTIVE step length Update strategy
• 年，卷（期）: 2017,（2）
• 页码范围: 105-106
• 页数: 2页
• 分类号: C5

摘要

Binary wolf pack algorithm (BWPA) is a kind of intelligence algorithm which can solve combination optimization problems in discrete spaces.Based on BWPA, an improved binary wolf pack algorithm (AIBWPA) can be proposed by adopting adaptive step length and improved update strategy of wolf pack. AIBWPA is applied to 10 classic 0-1 knapsack problems and compared with BWPA, DPSO, which proves that AIBWPA has higher optimization accuracy and better computational robustness. AIBWPA makes the parameters simple, protects the population diversity and enhances the global convergence.