Development of a decision support system for solving container loading problems

The globalization of supply chains and rising fuel costs are forcing container carriers both to minimize the number of trips and to maximize available container space. This makes container loading (CL) a critical process especially in real‐life applications. Container loading (CL), which is a difficult problem to be solved, has many applications in container transportation and distribution industries. This article presents a container loading support system (CLSS). The proposed CLSS composes of three main components, including a hybrid Bees Algorithm as the main computational algorithm, the graphical user interface (GUI) and a simulation program. The aim of the designed system is to make the packing pattern more visible to the user in order to simplify the loading process. An illustrative example ‐a CL problem from literature ‐ is also provided to introduce the operation of the system and to prove its efficiency. First published online: 24 Jun 201

Inteligencia de enjambres: sociedades para la solución de problemas (una revisión)

En este artículo se presenta una revisión de los conceptos de inteligencia de enjambres, y algunas perspectivas en la investigación con estas técnicas, con el objetivo de establecer un punto de partida para trabajos futuros en diferen-tes áreas de la ingeniería. Para la construcción de esta revisión se llevó a cabo una búsqueda bibliográfica en las bases de datos más actualizadas de los artículos clásicos del tema y de las últimas aplicaciones y resultados publi-cados, en particular en las áreas de control automático, procesamiento de señales e imágenes, y robótica, extra-yendo su concepto más relevante y organizándolo de manera cronológica. Como resultado se obtuvo taxonomía de la computación evolutiva, la diferencia entre la inteligencia de enjambres y otros algoritmos evolutivos, y una vi-sión amplia de las diferentes técnicas y aplicaciones.This paper presents a review of the basic concepts of swarm intelligence and some views regarding the future of re-search in this area aimed at establishing a starting point for future work in different engineering fields. A bibliogra-phic search of the most updated databases regarding classic articles on the subject and the most recent applications and results was used for constructing this review, especially in the areas of automatic control, signal and image pro-cessing and robotics. The main concepts were selected and organised in chronological order. A taxonomy was ob-tained for evolutionary computing techniques, a clear differentiation between swarm intelligence and other evolutio-nary algorithms and an overview of the different techniques and applications

A True Annealing Approach to the Marriage in Honey-Bees Optimization Algorithm

Marriage in Honey Bees Optimization (MBO) is a new swarm intelligence technique inspired by the marriage process of honey bees. It has been shown to be very effective in solving the propositional satisfiability problem known as 3--SAT (each clause has exactly three literals). The objective of this paper is to test a conventional annealing approach as a basis for determining the pool of drones (fathers). This modified MBO algorithm is tested using a group of randomly generated hard 3--SAT problems to compare its behavior and efficiency against previous implementations