TSALBP: Time and Space constrained Assembly Line Balancing Problems
Multiobjective memetic algorithms for time and space assembly line balancing
Authors
Manuel Chica2, Óscar Cordón2, Sergio Damas2 and Joaquín Bautista1
2 European Centre for Soft Computing
Abstract
This paper presents three proposals of multiobjective memetic algorithms to solve a more realistic extension of a classical industrial problem: time and space assembly line balancing. These three proposals are respectively based on evolutionary computation, ant colony optimization, and greedy randomised search procedure. Different variants of these memetic algorithms have been developed and compared in order to determine the most suitable intensification-diversification tradeoff for the memetic search process. Once a preliminary study on nine well-known problem instances is accomplished with a very good performance, the proposed memetic algorithms are applied considering real-world data from a Nissan plant in Barcelona (Spain). Outstanding approximations to the pseudo-optimal non-dominated solution set were achieved for this industrial case study.
Key words: Time and space assembly line balancing problem, automotive industry, multiobjective optimization, memetic algorithms, NSGA-II, ant colony optimization, GRASP, local search
