A multi-objective genetic optimization technique for the strategic design of distribution networks

Authors:
Vitoantonio Bevilacqua;Mariagrazia Dotoli;Marco Falagario;Fabio Sciancalepore;Stefano Saladino;Rocco Scaramuzzi
Affiliations:
Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Italy;Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Italy;Dipartimento di Ingegneria Meccanica e Gestionale, Politecnico di Bari, Italy;Dipartimento di Ingegneria Meccanica e Gestionale, Politecnico di Bari, Italy;Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Italy;Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Italy
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

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Abstract

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.