Research Article A Multiobjective Optimization Algorithm to Solve the Part Feeding Problem in Mixed-Model Assembly Lines Masood Fathi, 1 Maria Jesus Alvarez, 1 Farhad Hassani Mehraban, 2 and Victoria Rodríguez 3 1 Department of Industrial Organization, School of Engineering (TECNUN), University of Navarra, P ∘ Manuel Lardizabal 13, 20018 San Sebastian, Spain 2 Department of Management, King’s College London, 150 Stamford Street, London SE1 9NH, UK 3 Economics and Management School, University of Navarra, Campus Universitario, 31080 Pamplona, Spain Correspondence should be addressed to Masood Fathi; fathi.masood@gmail.com Received 27 November 2013; Accepted 6 February 2014; Published 20 May 2014 Academic Editor: Andrzej Swierniak Copyright © 2014 Masood Fathi et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Diferent aspects of assembly line optimization have been extensively studied. Part feeding at assembly lines, however, is quite an undeveloped area of research. Tis study focuses on the optimization of part feeding at mixed-model assembly lines with respect to the Just-In-Time principle motivated by a real situation encountered at one of the major automobile assembly plants in Spain. Te study presents a mixed integer linear programming model and a novel simulated annealing algorithm-based heuristic to pave the way for the minimization of the number of tours as well as inventory level. In order to evaluate the performance of the algorithm proposed and validate the mathematical model, a set of generated test problems and two real-life instances are solved. Te solutions found by both the mathematical model and proposed algorithm are compared in terms of minimizing the number of tours and inventory levels, as well as a performance measure called workload variation. Te results show that although the exact mathematical model had computational difculty solving the problems, the proposed algorithm provides good solutions in a short computational time. 1. Introduction In the contemporary business environment, assembly line designs have been following mixed-model assembly to respond to a variety of products. In general, in a mixed-model assembly line, for diferent versions, there are likely variations associated with base products. In this era, and for automotive manufacturers in partic- ular, mixed-model assembly lines are employed to produce a variety of submodels of the same automobile. Despite the many advantages of mixed-model assembly lines and its widespread use across the manufacturing plants, supplying these high-variant mixed-model lines has become a critical issue for managers as a huge number of parts/materials must be transferred to a location near the line (at stations) [1]. Moreover, a strong desire to provide an efcient Just-In-Time (JIT) parts supply, which aims to synchronize the supply of parts with their demand while avoiding shortages, has become another difculty as any shortage of parts might result in line stoppage and presumably an interruption of the production process. To deal with the challenges of this type as well as increase the reliability and fexibility of the part feeding process, a new concept—the so-called “supermarket”—was introduced, and it is utilized by many world-class manufacturers. Te supermarket is a decentralized logistics area near the assembly line where all parts/materials are sorted. Tis decentralized in-house logistics area enables the manufac- turers (especially those who are dealing with high-volume production) to ensure accessibility for a reliable small-lot JIT part delivery in assembly lines [2]. In particular, based on predefned production timelines, parts in the supermarket are transported to the shop foor in small bins and by means of tow trains (consisting of a small towing vehicle and a few wagons). Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2014, Article ID 654053, 12 pages http://dx.doi.org/10.1155/2014/654053