不确定多项目选址问题的微粒群优化算法

Particle Swarm Optimization for Uncertain Multi-project Location Problems

针对项目收益具有不确定性、为区间数的多项目选址问题,首先,定义约束的满足测度和处理策略,把含区间参数多目标优化模型转化为确定型单目标优化命题;接着,利用微粒群算法优化该模型,给出离散变量连续化、微粒位置归一化、微粒位置解码等关键问题的解决方法.最后,优化8项目10位置选址实例,验证了所建模型的可行性及算法的有效性。

Aiming at a multi-project location problem with uncertainty that the benefit values are intervals,firstly the multi-objective optimization model with interval parameters was converted into a certain single optimization proposition by defining a satisfaction metric and a solving method for constraints.Secondly,the particle swarm optimization algorithm was applied to solve the above model,based on that such continuity of discrete variables,normalization and decoding of particle positions as key problems were solved successfully.Finally,the feasibility of the deterministic model and the efficiency of the proposed algorithm were validated by optimizing an eight-project and ten-site location problem.