Handicapped Person Transportation: An application of the Grouping Genetic Algorithm

An effective method based on the Genetic Algorithms is proposed to solve the Handicapped Person Transportation problem, which is a real-life application for pickup and delivery problems. In these problems, vehicles have to transport (clients, loads, etc.) from their locations to different destinations (hospitals, shop centres, etc.). The objective of this paper is to implement Grouping Genetic Algorithm to find optimal (or close to optimal) routes for transporting handicapped people in terms of service quality and number of used vehicles. This algorithm is a stochastic search method based on randomized operators for combining solutions and producing better ones. The proposed algorithm has been applied on the handicapped persons transportation problem in the city of Brussels, Belgium. The obtained results are better than the manually generated solutions in terms of service quality and computational effort. © 2006 Elsevier Ltd. All rights reserved.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

A multiple objective grouping genetic algorithm for assembly line design

The purpose of this paper is to describe some of the main problems concerning assembly line design. The focus will be on the following steps: (1) the input data preparation, (2) the elaboration of the logical layout of the line, which consists in the distribution of operations among stations along the line and an assignment of resources to the different stations, (3) finally the mapping phase using a simulation package to check the obtained results. This work presents a new method to tackle the hybrid assembly line design, dealing with multiple objectives. The goal is to minimize the total cost of the line by integrating design (station space, cost, etc.) and operation issues (cycle time, precedence constraints, availability, etc.). This paper also presents in detail a very promising approach to solve multiple objective problems. It is a multiple objective grouping genetic algorithm hybridized with the multicriteria decision-aid method PROMETHEE II. An approach to deal with user's preferences in design problems is also introduced. The essential concepts adopted by the method are described and its application to an industrial case study is presented