Multi objective genetic algorithms for unequal area facility layout problems: A survey

The Unequal Area Facility Layout Problem (UA-FLP) comprises a class of extremely difficult and widely applicable optimization problems arising in diverse areas and meeting the requirements for real-world applications. In this paper we present our existing works of the past decade showing the evolutions obtained in the Genetic Algorithms (GA) used to solve the facility layout problem. GA have recently proven their effectiveness in finding (sub) optimal solutions to many NP-Hard problems such as UA-FLP. A main issue in such approach is related to the genetic encoding and to the evolutionary mechanism implemented, which must allow the efficient exploration of a wide solution space, preserving the feasibility of the solutions and ensuring the convergence towards the optimum. In addition, in realistic situations where several design issues must be taken into account, the layout problem falls in the broader framework of multi-objective optimization problems. Purpose In this paper, we present a recent survey about layout problems based on the research we have presented in the last ten years. In Section 1, we introduce the unequal area facility layout problems. Section 2 describes the multi objective genetic algorithm. The portioning structure of the layout and the relative genetic encoding scheme are reported in section 3. Section 4 shows the four objective functions employed in our approach and the ranking procedure used. The uncertainty which affects the layout problem in the decision making process is reported in Section 5. Finally, Section 6 concludes the paper with a short summary of the results obtained and describes the future developments of our research in this field. Design/methodology/approach The placement of the facilities in the plant area, often referred to as "facility layout problem", is known to have a significant impact upon manufacturing costs, work in process, lead times and productivity. A good placement of facilities contributes to the overall efficiency of operations and can reduce up to 50% the total operating expenses (Tompkins et al., 1996). Layout problems are known to be complex and are generally NP-Hard, as a consequence, a tremendous amount of research has been carried out in this area during the last decades. A few surveys have been published to review the different trends and research directions in this area, however, these surveys are either not recent (Drira et al. 2007). Originality/value The unequal area FLP has been an emerging topic in the recent years. A large volume of current research in unequal area FLPs has been conducted to satisfy both quantitative and qualitative aspects in the layout. In particular the topic of the Multi Objective optimization problems approached by Genetic Algorithms is nowadays one of the most promising and investigated research field. Further improvements of the proposed methodology will include the development of a more comprehensive procedure to approach the decision process, including the aspects related to the intrinsic uncertainty and referring to the typical methodologies of the approximate reasoning, such as the fuzzy theory