Genetic Algorithm for Optimization in Forest Industry Truck Scheduling

Velasquez Lobaton Enzo, Ramirez Valdez Oscar

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva


This paper presents the results obtained through research on travel scheduling defined by large forestry companies using a truck allocation system known as Asicam for the systematization of the transportation process. This system carries out an efficient programming of the transport of wood in the different centers, reducing transport costs to a minimum and respecting the technical, political and operational restrictions of the company. However, Asicam only optimizes at the strategic level, but not at the operational level. For this reason, the truck scheduling process can be improved. That is why an extension of the vehicle programming problem is introduced and a genetic algorithm is proposed that self-adapts its parameters to solve the problem. The objective is to optimize the round-trip journey by intelligently self-adjusting the entry parameters, which in turn will optimize travel time, system performance and company costs.

Idioma originalInglés
Título de la publicación alojadaAdvances in Information and Communication - Proceedings of the 2022 Future of Information and Communication Conference, FICC
EditoresKohei Arai
EditorialSpringer Science and Business Media Deutschland GmbH
Número de páginas18
ISBN (versión impresa)9783030980115
EstadoPublicada - 2022
EventoFuture of Information and Communication Conference, FICC 2022 - Virtual, Online
Duración: 3 mar. 20224 mar. 2022

Serie de la publicación

NombreLecture Notes in Networks and Systems
Volumen438 LNNS
ISSN (versión impresa)2367-3370
ISSN (versión digital)2367-3389


ConferenciaFuture of Information and Communication Conference, FICC 2022
CiudadVirtual, Online

Nota bibliográfica

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.


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