Ruteo de vehículos y programación de cargas en la distribución urbana de mercaderías con introducción de preferencias parciales en el proceso de toma de decisiones

Libro

Autoría:

MIGUEL, FABIO MAXIMILIANO ; FRUTOS, MARIANO ; TOHME, FERNANDO ABEL ; Méndez Babey, Máximo

Fecha:

2018

Editorial y Lugar de Edición:

Universidad Nacional del Sur

ISBN:

978-987-655-187-8

Resumen

This book is framed in the field of Operations, an area of Management Science. The goal is the development and validation of technological tools for decisionmaking in the logistic branch of supply chain management of the food industry. More specifically, we present a novel hybrid intelligent procedure aiding decisionmakers optimizing in a multi-objective environment. We examine the usual models of the physical distribution of goods, classifying them according to their main features. We also present the multi-objective evolutionary algorithms that usually yield the solutions to those models. Our approach is to introduce a new multiobjective variant of the distribution problem of goods in an urban area. To model the network of distribution centers, serving the final outlets of goods, we add time frames and other requirements. We consider the time dependence of the optimal programs of distribution, unlike the case of medium and long-distance logistical systems, for which the distance is the key criterion. We also add the objective of balancing loads among the different operating units. A hybridation of the multiobjective evolutionary algorithm NSGA-II is our choice of computational tool, jointly with the concept of g-dominance for partial preferences, which provides the informational guide in the search space. The validation and testing phases of this algorithm uses real-world data, comparing its outcomes to the results of other evolutionary multi-objective procedures used for the solution of complex problems of distribution. The information was provided by a logistic operator, specialized in transporting and distributing fractional loads. In all the cases examined, our algorithm performed better than the usual ones.

Palabras Clave

OPTIMIZACIÓNRUTEOMULTI-DEPÓSITOSLOGÍSTICA

Descargue o solicite el texto completo:

http://hdl.handle.net/11336/113827