基于粒子群算法的多目标背包问题求解  

Solving Multi-objective Knapsack Problem Based on Particle Swarm Optimization

作　　者：邓子龙[1] 程芳[1] DENG Zi-long;CHENG Fang(Anqing Vocational and Technical College, Anqing 246003, China)

机构地区：[1]安庆职业技术学院,安徽安庆246003

出　　处：《廊坊师范学院学报（自然科学版）》2018年第3期16-20,共5页Journal of Langfang Normal University(Natural Science Edition)

基　　金：2017年度安徽省高校优秀青年人才支持计划项目(gxyq2017212);2016年度安徽省自然科学研究项目(KJ2016A447)

摘　　要：多目标背包问题模型是多种优化问题的总结模型,对该模型的求解具有较强的现实意义。针对多目标背包问题,建立了多目标优化模型,利用粒子群算法进行求解,给出了算法求解的具体流程。最后,结合实例对算法性能进行了仿真分析,结果表明,多目标粒子群能够给出模型的非劣解集,实现多目标之间的折中权衡,能更有效地解决多目标背包问题。The multi-objective knapsack problem model is a summary model of multiple optimization problems, and solving this model has a strong practical significance. Aiming at the problem of multi-target knapsack, a multi-objective optimization model was established, the particle swarm algorithm was used to solve the problem, and the specific process of the algorithm was given. Finally, the algorithm performance was simulated and analyzed with an example. The simulation result shows that the multi-objective particle swarm is able to give the non-inferior solution set of the model, achieve more compromise between multiple goals, and solve the multi-objective knapsack problem more effectively.

关 键 词：粒子群 多目标 背包问题 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]