Facility layout planning. An extended literature review

[EN] Facility layout planning (FLP) involves a set of design problems related to the arrangement of the elements that shape industrial production systems in a physical space. The fact that they are considered one of the most important design decisions as part of business operation strategies, and their proven repercussion on production systems' operation costs, efficiency and productivity, mean that this theme has been widely addressed in science. In this context, the present article offers a scientific literature review about FLP from the operations management perspective. The 232 reviewed articles were classified as a large taxonomy based on type of problem, approach and planning stage and characteristics of production facilities by configuring the material handling system and methods to generate and assess layout alternatives. We stress that the generation of layout alternatives was done mainly using mathematical optimisation models, specifically discrete quadratic programming models for similar sized departments, or continuous linear and non-linear mixed integer programming models for different sized departments. Other approaches followed to generate layout alternatives were expert's knowledge and specialised software packages. Generally speaking, the most frequent solution algorithms were metaheuristics.The research leading to these results received funding from the European Union H2020 Program under grant agreement No 958205 `Industrial Data Services for Quality Control in Smart Manufacturing (i4Q)'and from the Spanish Ministry of Science, Innovation and Universities under grant agreement RTI2018-101344-B-I00 `Optimisation of zerodefectsproduction technologies enabling supply chains 4.0 (CADS4.0)'Pérez-Gosende, P.; Mula, J.; Díaz-Madroñero Boluda, FM. (2021). Facility layout planning. An extended literature review. International Journal of Production Research. 59(12):3777-3816. https://doi.org/10.1080/00207543.2021.189717637773816591

The aperiodic facility layout problem with time-varying demands and an optimal master-slave solution approach

In many seasonal industries, customer demands are constantly changing over time, and accordingly the facility layout should be re-optimized in a timely manner to adapt to changing material handling patterns among manufacturing departments. This paper investigates the aperiodic facility layout problem (AFLP) that involves arranging facilities layout and re-layout aperiodically in a dynamic manufacturing environment during a given planning horizon. The AFLP is decomposed into a master problem and a combination set of static facility layout problems (FLPs, the slave problems) without loss of optimality, and all problems are formulated as mixed-integer linear programming (MILP) models that can be solved by MIP solvers for small-sized problems. An exact backward dynamic programming (BDP) algorithm with a computational complexity of O(n 2) is developed for the master problem, and an improved linear programming based problem evolution algorithm (PEA-LP) is developed for the traditional static FLP. Computational experiments are conducted on two new problems and twelve well-known benchmark problems from the literature, and the experimental results show that the proposed solution approach is promising for solving the AFLP with practical sizes of problem instances. In addition, the improved PEA-LP found new best solutions for five benchmark problems

Heuristics for the dynamic facility layout problem with unequal area departments

The facility layout problem (FLP) is a well researched problem of finding positions of departments on a plant floor such that departments do not overlap and some objective(s) is (are) optimized. In this dissertation, the FLP with unequal area rectangular shaped departments is considered, when material flows between departments change during the planning horizon. This problem is known as the dynamic FLP. The change in material flows between pairs of departments in consecutive periods may require rearrangements of departments during the planning horizon in order to keep material handling costs low. The objective of our problem is to minimize the sum of the material handling and rearrangement costs. Because of the combinatorial structure of the problem, only small sized problems can be solved in reasonable time using exact techniques. As a result, construction and improvement heuristics are developed for the proposed problem. The construction algorithms are boundary search heuristics as well as a dual simplex method, and the improvement heuristics are tabu search and memetic heuristics with boundary search and dual simplex (linear programming model) techniques. The heuristics were tested on a generated data set as well as some instances from the literature. In summary, the memetic heuristic with the boundary search technique out-performed the other techniques with respect to solution quality

Genetic approaches for the unequal area facility layout problem

Esta tesis doctoral aborda el problema de distribución en planta, el cuál en líneas generales, pretende asignar o distribuir instalaciones en una planta industrial. Existen muchos problemas diferentes dependiendo de las características que sean consideradas de la planta industrial, como por ejemplo, la forma de las instalaciones, el número de plantas, la flexibilidad requerida en los sistemas de producción, el tipo de producto que se fabrica, etcétera. Uno de los problemas más abordados, ha sido el problema de distribución en planta con instalaciones de área desigual. Para solucionar este tipo problemas existen muchas técnicas que pretenden alcanzar un diseño eficiente de la planta industrial. Entre ellas, una de las estrategias más usadas por los investigadores ha sido la de los Algoritmos Genéticos (AGs). Los AGs requieren definir un esquema de codificación para representar el diseño de la planta industrial como una estructura de datos. Esta estructura determina el tipo de soluciones que pueden ser obtenidas, e influencia la capacidad del AG para encontrar buenas soluciones. Aunque existen varios trabajos que revisan el estado del arte de los problemas de distribución en planta, no hay ninguno que centre su revisión en los esquemas de codificación y los operadores evolutivos usados por los AGs. Así, una de las contribuciones de la tesis que se presenta, es el estudio de los esquemas de codificación y los operadores evolutivos empleados por los AGs en problemas de distribución en planta. Además, este estudio se completa con una clasificación de las diferentes estructuras de codificación utilizadas por los autores, un estudio de sus características y objetivos, y finalmente, la identificación de los operadores de cruce y mutación que pueden ser aplicados dependiendo de la estructura de codificación. Por otro lado, en esta tesis se propone un AG para el problema de distribución en planta de instalaciones de área desigual, teniendo en cuenta aspectos que pueden ser cuantificados, tales como: el de flujo de material, las relaciones lógicas entre las actividades que se realizan en los centros de producción (comúnmente, instalaciones) y la forma de cada uno. Para ello, se sugiere una nueva forma de representar las plantas industriales. Este algoritmo se ha integrado en una aplicación informática que permite a los usuarios introducir los datos y configurar los parámetros del algoritmo, así como mostrar las soluciones propuestas de una manera sencilla y amigable. Finalmente, el algoritmo ha sido probado con varios problemas y sus resultados comparados con los obtenidos en otros trabajos citados en la bibliografía. Aunque el problema de distribución en planta de instalaciones de área desigual ha sido resuelto con muchas estrategias, siempre ha sido abordado teniendo en cuenta criterios cuantificables. Sin embargo, existen características subjetivas que resultan muy interesantes para este problema. Dicha características son muy difíciles de tener en cuenta mediante los métodos clásicos de optimización. Por esta razón, se propone un Algoritmo Genético Interactivo (AGI) para el problema de distribución en planta de instalaciones de área desigual, el cuál permite la interacción entre el algoritmo y el diseñador. Con la implicación del conocimiento del diseñador en la propuesta, el proceso de búsqueda es guiado y ajustado a las preferencias de aquél en cada iteración del algoritmo. Para evitar sobrecargar al diseñador, la población de soluciones es clasificada en grupos mediante un método de clustering. Así, sólo un elemento de cada grupo es evaluado. Durante todo este proceso, aquellas soluciones que resulten interesantes para el diseñador son almacenadas en memoria. Las pruebas realizadas muestran que el AGI propuesto es capaz de captar las preferencias del diseñador, y que además, progresa hacia una buena solución en un número de iteraciones razonable

A layout design decision-support framework and concept demonstrator for rural hospitals using mixed methods

Thesis (MEng)--Stellenbosch University, 2017.ENGLISH ABSTRACT: Layout design is an ever-present problem that has a significant effect on the operations of an organisation, especially in the context of healthcare which deals with the lives of patients. It is a complex problem that has long-term consequences and oftentimes competing objectives. Literature has focused almost exclusively on using either quantitative or qualitative layout design methods for designing layouts. This study develops a generic framework using both quantitative and qualitative layout design methods that will guide the user to design a near optimal layout for a rural hospital while taking into consideration the relevant laws and standards as well as the health outcomes of the surrounding rural community. Rural and urban lifestyles, health, and illnesses differ in many ways. General hospital design methods are therefore not necessarily appropriate for hospitals in these areas. There is thus a need for a framework to be tailored for a rural community. Following a mixed methods methodology, a systematic literature review of quantitative and qualitative layout design methods along with hospital design considerations were conducted in order to determine the most adequate methods for designing a hospital layout at the block diagram level of detail. Furthermore, the commonalities and differences between rural and urban hospitals were investigated including laws and standards relevant to hospital layouts. The qualitative layout design methods involved different layout procedures and Muther’s Systematic Layout Planning Procedure was found to be most adequate. Furthermore, hospital design considerations such as patient-centeredness, efficiency, flexibility and expandability, sustainability, and therapeutic environment were identified and linked with the quantitative layout methods. It was also found that rural communities have different needs to urban ones with regard to access to medical care, prominent illnesses, and attitudes towards health. The healthcare personnel shortages are particularly problematic for rural communities. The quantitative layout design methods involved layout models, solution methods (exact methods, metaheuristics, and hybrid metaheuristics), and layout software. Using criteria of objectives, assumptions, inputs, outputs, and hospital design considerations, the Quadratic Set Covering Problem was determined to be the most appropriate model for designing a rural hospital block diagram layout. It was deemed possible to integrate the quantitative and qualitative methods by embedding the qualitative data into this quantitative model. The rural hospital design framework was developed using Excel VBA and RStudio. The framework was validated via two routes. Firstly, semi-structured interviews were conducted with experts in the field, i.e. expert analyses. Secondly a case study of the Semonkong Hospital Project was employed wherein the framework was applied successfully. The framework was deemed valid according to both the expert analyses and the case study.AFRIKAANSE OPSOMMING: Die uitleg van ‘n gebou het ‘n belangrike impak op die bedrywighede van ‘n organisasie – veral in die konteks van gesondheidsorg waar daar met pasiënte se lewens gewerk word. Dit is ‘n ingewikkelde probleem wat oor langtermyneffekte beskik en dikwels teenstrydige doelwitte. Die literatuur vir uitleg ontwerpsmetodes het meestal gefokus op óf kwantitatiewe óf kwalitatiewe uitleg ontwerpsmetodes. Hierdie studie ontwikkel ‘n generiese raamwerk wat beide van hierdie metodes gebruik om ‘n gebruiker te lei om die uitleg van ‘n plattelandse hospital te ontwerp wat die gepaste wette en standaarde en die gesondheid van die omliggende gemeenskap in ag neem. Landelike- en stedelike gemeenskappe verskil in terme van hul lewenstyl, gesondheid en tipe siektes. Algemene uitleg ontwerpsmetodes is dus nie noodwendig geskik vir ‘n plattelandse hospitaal nie. Daar is dus ‘n behoefte om ‘n raamwerk te ontwikkel wat spesifiek is vir die uitleg van ‘n plattelandse hospitaal. Hierdie studie volg ‘n gemengde metode benadering en ‘n sistematiese literatuurstudie is gevolglik afsonderlik gedoen op kwantitatiewe- en kwalitatiewe uitleg ontwerpsmetodes met die doel om die mees geskikte ontwerpsmetodes vir ‘n hospitaal uitleg te bepaal. Die verskille en ooreenkomste tussen landelike- en stedelike hospitale was ook ondersoek. Hierdie sluit in wette en standaarde wat van toepassing is op hospitaal uitlegte. Die kwalitatiewe uitleg ontwerpsmetodes het verskillende uitleg prosedures ondersoek en dit is gevind dat Muther se Sistematiese Uitleg Prosedure die mees geskik is vir die probleem van hierdie studie. Daar is gevind dat die hoof ontwerpsoorwegings vir die uitleg van ‘n hospitaal pasiënt-gesentreerdheid, doeltreffendheid, aanpasbaarheid, volhoubaarheid en terapeutiese omgewing is. Daar is gevind dat landelike- en stedelike gemeenskappe verskil in terme van hul toegang tot mediese sorg, prominente siektes, en hul houdings teenoor gesondheid. Een van die grootste probleme in landelike hospitale was hul tekort aan personeel. Die kwantitatiewe uitleg ontwerpsmetodes sluit uitleg modelle, oplossingsmetodes (presiese metodes, metaheuristieke en hibriede metaheuristieke) en uitleg sagteware in. ‘n Kriteria van doelwitte, aannames, insette, uitsette en hospitaal ontwerpsoorwegings was gebruik om die mees geskikte uitleg model te kies naamlik: die ‘Quadratic Set Covering Problem’. Dit is gevind dat die kwantitatiewe- en kwalitatiewe uitleg ontwerpsmetodes deur middel van ‘embedding’ geïntegreer kan word. Die uitleg ontwerp raamwerk vir plattelandse hospitale was ontwikkel met behulp van Excel VBA en RStudio. Die raamwerk is bekragtig deur twee roetes. Eerstens, semi-gestruktureerde onderhoude was gevoer met kundiges in die velde van gesondheidsorg, plattelandse gemeenskappe en uitleg ontwerp. Tweedens, die raamwerk is toegepas op ‘n gevallestudie van die Semonkong Hospitaal Projek. Albei roetes dui daarop dat die raamwerk geldig is

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Heuristic scheduling algorithms for dedicated and flexible manufacturing systems

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