A Multi-objective Genetic Optimization Technique for the Strategic Design of Distribution Networks

被引:0
作者
Bevilacqua, Vitoantonio [1 ]
Dotoli, Mariagrazia [1 ]
Falagario, Marco [2 ]
Sciancalepore, Fabio [2 ]
D'Ambruoso, Dario [1 ]
Saladino, Stefano [1 ]
Scaramuzzi, Rocco [1 ]
机构
[1] Politecn Bari, Dipartimento Elettrotecn & Elettron, Bari, Italy
[2] Politecn Bari, Dipartimento Ingn Meccan & Gest, Bari, Italy
来源
ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE | 2012年 / 6839卷
关键词
SUPPLY CHAIN; ALGORITHM;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We address the optimal design of a Distribution Network (DN), presenting a procedure employing Multi-Objective Genetic Algorithms (MOGA) to select the (sub) optimal DN configuration. Using multi-objective genetic optimization allows solving a nonlinear design problem with piecewise constant contributions in addition to linear ones. The MOGA application allows finding a Pareto frontier of (sub) optimal solutions, which is compared with the frontier obtained solving the same problem with linear programming, where piecewise constant contributions are linearly approximated. The two curves represent, respectively, the upper and the lower limit of the region including the real Pareto curve. Both the genetic optimization model and the linear programming are applied under structural constraints to a case study describing the DN of an Italian enterprise.
引用
收藏
页码:243 / +
页数:2
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