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. Genetic Algorithms (GAs) 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. To date, there are only a few multi-objective FLP approaches, and most of them employ over-simplified optimization techniques which eventually influence the quality of the solutions obtained and the performance of the optimization procedure. In this paper, this difficulty is overcome by approaching the problem in two subsequent steps: in the first step, the Pareto-optimal solutions are determined by employing Multi Objective Genetic Algorithm (MOGA) implementing four separate fitness functions within a Pareto evolutionary procedure, following the general structure of Non-dominated Ranking Genetic Algorithm (NRGA) and the subsequent selection of the optimal solution is carried out by means of the multi-criteria decision-making procedure Electre. This procedure allows the decision maker to express his preferences on the basis of the knowledge of candidate solution set. Quantitative and qualitative objectives are considered referring to the slicing-tree layout representation scheme. The numerical results obtained outperform previous referenced approaches, thus confirming the effectiveness of the procedure proposed.

A non dominated ranking Multi Objective Genetic Algorithm and electre method for unequal area facility layout problems

The unequal area facility layout problem UA-FLP has been addressed by many methods. Most of them only take aspects that can be quantified into account. This contribution presents a novel approach, which considers both quantitative aspects and subjective features. To this end, a multi-objective interactive genetic algorithm is proposed with the aim of allowing interaction between the algorithm and the human expert designer, normally called the decision maker DM in the field of UA-FLP. The contribution of the DM's knowledge into the approach guides the complex search process, adjusting it to the DM's preferences. The entire population associated to facility layout designs is evaluated by quantitative criteria in combination with an assessment prepared by the DM, who gives a subjective evaluation for a set of representative individuals of the population in each iteration. In order to choose these individuals, a soft computing clustering method is used. Two interesting real-world data sets are analysed to empirically probe the robustness of these models. The first UA-FLP case study describes an ovine slaughterhouse plant and the second, a design for recycling carton plant. Relevant results are obtained, and interesting conclusions are drawn from the application of this novel intelligent framework.

/pdf/facility-layout-design-using-a-multi-objective-interactive-1n3j95ip7c.pdf

Facility layout design using a multi-objective interactive genetic algorithm to support the DM

Facility Layout Design is known to be very important for attaining production efficiency because it directly influences manufacturing costs, lead times, work in process and productivity. Facility Layout problems have been addressed using several approaches. Unfortunately, these approaches only take into account quantitative criteria. However, there are qualitative preferences referred to the knowledge and experience of the designer, which should also be considered in facility layout design. These preferences can be subjective, not known in advance and changed during the design process, so that, it is difficult to include them using a classic optimization approach. For that reason, we propose the use of an Interactive Genetic Algorithm (IGA) for designing the layout of two real recycling plants taking into consideration subjective features from the designer. The designer's knowledge guides the evolution of the algorithm evaluating facility layouts in each generation adjusting the search to his/her preferen...

Recycling Plants Layout Design by Means of an Interactive Genetic Algorithm

Purpose




The design of retail backroom storage areas has great impact on in-store operations, customer service level and on store life-cycle costs. Moreover, backroom storage in modern retail grocery stores is critical to several functions, such as acting as a buffer against strong demand lifts yielded by an ever-increasing promotional activity, stocking seasonal peak demand and accommodating e-commerce activities. The purpose of this paper is to propose a framework to design retail backroom storage area. Furthermore, the authors aim to draw attention to the lack of literature on this topic, while clarifying the relationship between this promising research stream and the considerable body of research regarding the design and operations of conventional warehouses, as well as retail in-store operations.




Design/methodology/approach




The key literature on backrooms, grocery retail, in-store operations, warehouse design and operations was reviewed. This allowed an understanding of the gap in the literature regarding the design of backrooms. Moreover, a case study methodological approach was conducted in a Portuguese retailer to extend the literature review.




Findings




Despite having functions similar to conventional warehouses, backroom storage facilities have particularities that deserve a distinct analysis. Thus, the authors stress these differences and demonstrate how they influence the development of a novel backroom design framework.




Originality/value




This paper fills a gap by proposing a framework to design backroom areas. Furthermore, this research may help practitioners to better design backroom areas, since this process currently lacks a formal and standardized procedure.

/pdf/a-framework-for-designing-backroom-areas-in-grocery-stores-3wm3fzgx30.pdf

A framework for designing backroom areas in grocery stores

Characterization of biodiesel using virtual laboratories integrating social networks and web app following a ubiquitous- and blended-learning

Unequal Area Facility Layout Problem (UA-FLP) is a relevant problem with industrial application and it has been addressed by several methods having into account only quantitative criteria. This contribution presents an approach to consider subjective features in UA-FLP. An Interactive Genetic Algorithm (IGA) is proposed that allows interaction between the algorithm and the Decision Maker (DM). The participation of the DM knowledge into the approach guides the search process, adjusting it to the DM’s preferences at every iteration of the algorithm. The whole population is evaluated by the DM through subjective evaluation of the representative individuals. In order to choose this individuals, a soft computing clustering method is used. The empirical evaluation shows that the proposed IGA is capable of capturing DM preferences and it can progress towards a good solution in a reasonable number of iterations to avoid the user tiredness.

An Interactive Genetic Algorithm for the Unequal Area Facility Layout Problem

This work presents a web portal for telematic training in work-related risk prevention: noise at work and machine vibrations. Training in Work-related Risk Prevention, especially in the area of Industrial Hygiene, has a practical laboratory component, which is fundamental for a correct preparation of prevention technicians so that they can become acquainted with the field equipment that they have to use in risk evaluation, its configuration, principal parts and handling; everything from its calibration to its application in measuring as a function of the job’s conditions, always within the correct methodological application dictated by the national and international norms which regulate these field applications. This signifies important time expenditure for specialist teachers and in field equipment for the users being trained. With virtual laboratories containing the web application developed it is aimed to complement experimental laboratory training, with simulative tools which provide the knowledge and the practical handling of the equipment under the most real conditions possible, thus considerably reducing the number of laboratory hours necessary. It is a matter of having a catalogue of virtual laboratories with a free and easy access, the one in the first stage being specifically that corresponding to noise at work.

Lorenzo Salas Morera

Papers

An Interactive Genetic Algorithm for the Unequal Area Facility Layout Problem

Telematic training via a website of technicians in work-related risk prevention