The Experts below are selected from a list of 10149 Experts worldwide ranked by ideXlab platform
Kuan Yew Wong - One of the best experts on this subject based on the ideXlab platform.
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Solving unequal-area static and dynamic Facility Layout problems using modified particle swarm optimization
Journal of Intelligent Manufacturing, 2017Co-Authors: Ali Derakhshan asl, Kuan Yew WongAbstract:Facility Layout problems deal with Layout of facilities or departments in a shop floor. This article studies unequal-area static Facility Layout problems in order to minimize the sum of the material handling costs and unequal-area dynamic Facility Layout problems so as to minimize the sum of the material handling costs and rearrangement costs. Unequal-area static and dynamic Facility Layout problems are NP-hard. Therefore, a modified particle swarm optimization was suggested to solve them where the departments have fixed shapes and areas throughout the time horizon. The modified particle swarm optimization was tested using the available problem instances chosen from the literature. The proposed algorithm applied two local search methods and the department swapping method to improve the quality of solutions and to prevent local optima for dynamic and static problems. It also utilized the period swapping method to improve the solutions for dynamic problems. The results showed that the proposed algorithm has created encouraging Layouts in comparison with other approaches.
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unequal area stochastic Facility Layout problems solutions using improved covariance matrix adaptation evolution strategy particle swarm optimisation and genetic algorithm
International Journal of Production Research, 2016Co-Authors: Ali Derakhshan Asl, Kuan Yew Wong, Manoj Kumar TiwariAbstract:Determining the locations of departments or machines in a shop floor is classified as a Facility Layout problem. This article studies unequal-area stochastic Facility Layout problems where the shapes of departments are fixed during the iteration of an algorithm and the product demands are stochastic with a known variance and expected value. These problems are non-deterministic polynomial-time hard and very complex, thus meta-heuristic algorithms and evolution strategies are needed to solve them. In this paper, an improved covariance matrix adaptation evolution strategy (CMA ES) was developed and its results were compared with those of two improved meta-heuristic algorithms (i.e. improved particle swarm optimisation [PSO] and genetic algorithm [GA]). In the three proposed algorithms, the swapping method and two local search techniques which altered the positions of departments were used to avoid local optima and to improve the quality of solutions for the problems. A real case and two problem instances wer...
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short communication solving Facility Layout problems using flexible bay structure representation and ant system algorithm
Expert Systems With Applications, 2010Co-Authors: Kuan Yew WongAbstract:This paper proposes an Ant System (AS) algorithm for solving Unequal Area Facility Layout Problems (UA-FLPs) using Flexible Bay Structure (FBS) representation. In addition, an improvement to the FBS representation is made when solving problems with empty spaces. The method is extensively tested using numerous problem instances taken from the literature and overall, encouraging results are obtained.
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applying ant system for solving unequal area Facility Layout problems
European Journal of Operational Research, 2010Co-Authors: Kuan Yew WongAbstract:Ant Colony Optimization (ACO) is a young metaheuristic algorithm which has shown promising results in solving many optimization problems. To date, a formal ACO-based metaheuristic has not been applied for solving Unequal Area Facility Layout Problems (UA-FLPs). This paper proposes an Ant System (AS) (one of the ACO variants) to solve them. As a discrete optimization algorithm, the proposed algorithm uses slicing tree representation to easily represent the problems without too restricting the solution space. It uses several types of local search to improve its search performance. It is then tested using several case problems with different size and setting. Overall, the proposed algorithm shows encouraging results in solving UA-FLPs.
Henri Pierreval - One of the best experts on this subject based on the ideXlab platform.
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dynamic Facility Layout problem based on open queuing network theory
European Journal of Operational Research, 2017Co-Authors: Hani Pourvaziri, Henri PierrevalAbstract:Abstract Determining the location of machines for given periods of time, depending on changes in the material flow between the machines, is known in the literature as a dynamic Facility Layout problem (DFLP). While most approaches focus on reducing handling and rearrangement costs, this article also considers the amount of work-in-process (WIP) for a particular class of problems. WIP results from the queuing phenomenon and depends on the availability of transportation units. To solve these types of problems, we suggest the use of an analytical approach which uses open queuing network theory and is based on a quadratic assignment problem formulation. Since a queuing model approximates the studied system, the accuracy of the results is evaluated through a comparison with simulation results. Considering both the NP-hardness and the multi-objective nature of the problem, a meta-heuristic optimization approach is proposed. It aims at determining the Pareto front using cloud-based multi-objective simulated annealing (C-MOSA). The performance of C-MOSA is evaluated against other published multi-objective approaches. Computational experiments are performed and the results show that C-MOSA is capable of obtaining efficient results to solve the multi-objective dynamic Facility Layout problem.
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a novel hybrid evolutionary approach for capturing decision maker knowledge into the unequal area Facility Layout problem
Expert Systems With Applications, 2015Co-Authors: Laura Garciahernandez, Lorenzo Salasmorera, Juan M Palomoromero, Antonio Arauzoazofra, Henri PierrevalAbstract:We are concerned with an unequal area Facility Layout problem.Existing approaches are normally based on optimization, which can be insufficient in certain cases.Our interactive genetic algorithm involves the decision maker in the search for a suited solution.Our new approach based on niching methods is tested with two real problem cases. Introducing expert knowledge into evolutionary algorithms for the Facility Layout design problem can provide better solutions than the mathematically optimal solutions by considering qualitative aspects in the design. However, this approach requires the direct intervention of a designer (normally called the decision maker) in the evolutionary algorithm that guides the search process to adjust it to his/her preferences. To do this, the designer scores each of the most representative designs of the population to avoid fatigue. The selection of the solutions to be presented for human assessment is crucial, so a small number of solutions that represents the characteristics of the population must be selected without losing the variability of the solutions. The novel hybrid system proposed in this study consists of an interactive genetic algorithm that is combined with two different niching methods to allow interactions between the algorithm and the expert designer. The inclusion of niching techniques into the approach allows for the preservation of diversity, which avoids presenting similar solutions to the designer in the same iteration of the algorithm. The proposed approach was tested using two case studies of Facility Layout designs. The results of the experiments, which successfully validate the approach, are presented, compared and discussed.
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Facility Layout design using a multi objective interactive genetic algorithm to support the dm
Expert Systems, 2015Co-Authors: Laura Garciahernandez, Henri Pierreval, Lorenzo Salasmorera, Antonio Arauzoazofra, Emilio CorchadoAbstract: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.
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Facility Layout problems a survey
Annual Reviews in Control, 2007Co-Authors: Henri Pierreval, Amine Drira, Sonia HajrigaboujAbstract:Layout problems are found in several types of manufacturing systems. Typically, Layout problems are related to the location of facilities (e.g., machines, departments) in a plant. They are known to greatly impact the system performance. Most of these problems are NP hard. Numerous research works related to Facility Layout have been published. A few literature reviews exist, but they are not recent or are restricted to certain specific aspects of these problems. The literature analysis given here is recent and not restricted to specific considerations about Layout design. We suggest a general framework to analyze the literature and present existing works using such criteria as: the manufacturing system features, static/dynamic considerations, continual/discrete representation, problem formulation, and resolution approach. Several research directions are pointed out and discussed in our conclusion. # 2007 Elsevier Ltd. All rights reserved.
Surya Prakash Singh - One of the best experts on this subject based on the ideXlab platform.
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integrating big data analytic and hybrid firefly chaotic simulated annealing approach for Facility Layout problem
Annals of Operations Research, 2018Co-Authors: Akash Tayal, Surya Prakash SinghAbstract:Manufacturing industries have become larger, diverse and the factors affecting a Facility Layout design have grown rapidly. Handling and evaluating these large set of criteria (factors) is difficult in designing and solving Facility Layout problems. These factors and uncertainties have a large impact on manufacturing time, manufacturing cost, product quality and delivery performance. In order to operate efficiently, these facilities should adapt to these variations over multiple time periods and this must be addressed while designing an optimal Layout. This paper proposes a novel integrated framework by combining Big Data Analtics and Hybrid meta-heuristic approach to design an optimal Facility Layout under stochastic demand over multiple periods. Firstly, factors affecting a Facility Layout design are identified. The survey is conducted to generate data reflecting 3V’s of Big Data. Secondly, a reduced set of factors are obtained using Big Data Analytics. These reduced set of factors are considered to mathematically model a weighted aggregate objective for Multi-objective Stochastic Dynamic Facility Layout Problem (MO-SDFLP). Hybrid Meta-heuristic based on Firefly (FA) and Chaotic simulated annealing is used to solve the MO-SDFLP. To show the working methodology of proposed integrated framework an exemplary case is presented.
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formulating and solving sustainable stochastic dynamic Facility Layout problem a key to sustainable operations
Annals of Operations Research, 2017Co-Authors: Akash Tayal, Angappa Gunasekaran, Surya Prakash Singh, Rameshwar Dubey, Thanos PapadopoulosAbstract:Facility Layout design, a NP hard problem, is associated with the arrangement of facilities in a manufacturing shop floor, which impacts the performance, and cost of system. Efficient design of Facility Layout is a key to the sustainable operations in a manufacturing shop floor. An efficient Layout design not only optimizes the cost and energy due to proficient handling but also increase flexibility and easy accessibility. Traditionally, it is solved using meta-heuristic techniques. But these algorithmic or procedural methodologies do not generate effective and efficient Layout design from sustainable point of view, where design should consider multiple criteria such as demand fluctuations, material handling cost, accessibility, maintenance, waste and more. In this paper, to capture the sustainability in the Layout design these parameters are considered, and a new sustainable stochastic dynamic Facility Layout problem (SDFLP) is formulated and solved. SDFLP is optimized for material handling cost and rearrangement cost using various meta-heuristic techniques. The pool of Layouts thus generated are then analyzed by data envelopment analysis to identify efficient Layouts. A novel hierarchical methodology of consensus ranking of Layouts is proposed which combines the multiple attributes/criteria. Multi attribute decision-making techniques such as technique for order preference by similarity to ideal solution, interpretive ranking process and analytic hierarchy process, Borda–Kendall and integer linear programming based rank aggregation techniques are applied. To validate the proposed methodology data sets for Facility size $$N=12$$ for time period $$T=5$$ having Gaussian demand are considered.
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optimal selection of multi criteria unequal area Facility Layout problem an integer linear program and borda kendall based method
International Journal of Business and Systems Research, 2017Co-Authors: Ravi Kumar, Surya Prakash SinghAbstract:The paper attempts to solve multi-criteria unequal area Facility Layout problem. Six criteria viz. distance, adjacency, shape ratio, flexibility, accessibility and maintenance are considered here. The unequal area Facility Layout is solved using a software SPIRAL where the data is taken from published literature. Several alternatives are generated by varying quantitative parameters but keeping the same objective function value. The optimal decision to select the best Facility Layout is decided based on six qualitative criteria. Multi-criteria decision making (MCDM) techniques AHP and IRP are applied on all alternative Layouts and the ranking of alternatives are obtained. In addition, weighted IRP method is also proposed to rank the available Layouts. AHP-IRP and weighted IRP provide independent ranking. For optimal selection of multi-criteria unequal area Facility Layout, an integer linear program (ILP) and Borda-Kendall (BK) method are applied. Integer linear program and Borda-Kendall method are applied to aggregate the various rankings of Facility Layouts for final decision.
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an improved heuristic approach for multi objective Facility Layout problem
International Journal of Production Research, 2010Co-Authors: Surya Prakash Singh, V K SinghAbstract:Multi-objective Facility Layout problem (mFLP) generates a different Layout by varying objectives weights. Since the selection of objective weights in mFLP is critical, stages of designing Layout having multiple objectives, the objective weights therefore play an important role in the Layout design of mFLP. In practice, it is selected randomly by the Layout designer based on his/her past experience that restricts the Layout designing process completely designer dependent and thus the Layout varies from designer to designer. This paper aims to resolve the issues of selecting the objective weight for each objective. We propose four methods to determine objective weight which makes the design process of mFLP completely designer independent.
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two level modified simulated annealing based approach for solving Facility Layout problem
International Journal of Production Research, 2008Co-Authors: Surya Prakash Singh, R. R. K. SharmaAbstract:In this paper, we are considering the quadratic assignment model (QAP) of the Facility Layout problem (FLP) which is known to be NP-hard. We relax the integer constraints of the QAP and solve it on a commercially available package called LINGO 8. In the optimal solution so obtained, Xij s take real values between zero and one. We identify promising Xij s having a value strictly greater than 0.5 in the optimal solution and set them to one. We add the constraints (Xij = 1) associated with promising Xij s into the QAP (with integer restrictions) and resolve using LINGO 8. In all the cases attempted we obtained a superior feasible solution to the QAP which was further improved by the proposed modified simulated annealing (MSA) procedure. An encouraging comparative performance of this procedure is thus reported.
S Jiang - One of the best experts on this subject based on the ideXlab platform.
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multi objective particle swarm optimization algorithm based on objective space division for the unequal area Facility Layout problem
Expert Systems With Applications, 2018Co-Authors: Jingfa Liu, Huiyun Zhang, S JiangAbstract:A model of the unequal-area Facility Layout problem is described.A modified multi-objective particle swarm optimization algorithm is proposed.We apply the heuristic strategy to update Layout.The gradient method is applied to execute local search.The objective space division method is used to find the Pbest and Gbest. The Facility Layout problem (FLP) is the problem of placing facilities in a certain shop floor so that facilities do not overlap each other and are satisfied with some given objectives. Considering practical situations, this study focuses on the multi-objective unequal-area Facility Layout problem (UA-FLP), where the facilities have unequal-areas and fixed shapes and are placed orthogonally in the continuous shop floor. The objectives of the problem aim to optimize the material handling cost, the total adjacency value and the utilization ratio of the shop floor. The chief difficulties of this version of the FLP lie in the satisfaction of non-overlapping constraint between any two different facilities and the optimization of multiple objectives in the huge solution space. In this paper, we put forward a heuristic configuration mutation operation and subsequent local search based on the gradient method to satisfy the non-overlapping constraint, and the multi-objective particle swarm optimization (MOPSO) algorithm, which has recently proven its high effectiveness and robustness in solving multi-objective problems, to obtain a set of Pareto-optimal solutions of the problem. The novelty of the paper lies in the use of an objective space division method in the MOPSO which governs the neighborhood topology and the local best swarm used to assess the global fitness of a solution and choose the global leader particle. The proposed algorithm is tested on three sets of different UA-FLPs from the literature with the size of the problem up to 62 facilities. The numerical results show that the proposed method is effective in solving the multi-objective UA-FLP.
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a novel Facility Layout planning and optimization methodology
CIRP Annals, 2013Co-Authors: S Jiang, A Y C NeeAbstract:Abstract This paper presents a novel factory planning system for real-time on-site Facility Layout planning (FLP). Two Facility Layout planning modules are supported, viz., manual and automatic. In this system, a fast modelling method has been developed where users can construct existing facilities as virtual primitive models. A criterion and constraint definition mechanism is provided to define and customize the planning criteria and constraints to suit specific requirements of different FLP tasks, and an Analytical Hierarchy Process–Genetic Algorithm (AHP–GA) based optimization scheme is adopted for automatic Layout planning. Augmented reality (AR) is used to provide visualization of the Layout process.
Andre Renato Sales Amaral - One of the best experts on this subject based on the ideXlab platform.
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a polyhedral approach to the single row Facility Layout problem
Mathematical Programming, 2013Co-Authors: Andre Renato Sales Amaral, Adam N LetchfordAbstract:The single row Facility Layout problem (SRFLP) is the NP-hard problem of arranging facilities on a line, while minimizing a weighted sum of the distances between Facility pairs. In this paper, a detailed polyhedral study of the SRFLP is performed, and several huge classes of valid and facet-inducing inequalities are derived. Some separation heuristics are presented, along with a primal heuristic based on multi-dimensional scaling. Finally, a branch-and-cut algorithm is described and some encouraging computational results are given.
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a new lower bound for the single row Facility Layout problem
Discrete Applied Mathematics, 2009Co-Authors: Andre Renato Sales AmaralAbstract:Single row Facility Layout is the NP-hard problem of arranging n departments of given lengths on a line so as to minimize the weighted sum of the distances between department pairs. In this paper, we define a polytope associated to the problem and present a partial linear description whose integral points are the incidence vectors of a Layout. We propose a new lower bound for the problem by optimizing a linear program over the partial description given and using some valid inequalities, which are introduced here, as cutting planes. Several instances from the literature as well as new large instances with size n=33 and n=35 are considered in the computational tests. For all the instances tested, the proposed lower bound achieves the cost of an optimal Layout within reasonable computing time.
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an exact approach to the one dimensional Facility Layout problem
Operations Research, 2008Co-Authors: Andre Renato Sales AmaralAbstract:The one-dimensional Facility Layout problem is concerned with arranging n departments of given lengths on a line, while minimizing the weighted sum of the distances between all pairs of departments. The problem is NP-hard because it is a generalization of the minimum linear arrangement problem. In this paper, a 0-1 quadratic programming model consisting of only O(n2) 0-1 variables is proposed for the problem. Subsequently, this model is cast as an equivalent mixed-integer program and then reduced by preprocessing. Next, additional redundant constraints are introduced and linearized in a higher space to achieve an equivalent mixed 0-1 linear program, whose continuous relaxation provides an approximation of the convex hull of solutions to the quadratic program. It is shown that the resulting mixed 0-1 linear program is more efficient than previously published mixed-integer formulations. In the computational results, several problem instances taken from the literature were efficiently solved to optimality. Moreover, it is now possible to efficiently solve problems of a larger size.
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on the exact solution of a Facility Layout problem
European Journal of Operational Research, 2006Co-Authors: Andre Renato Sales AmaralAbstract:We consider the Layout problem of arranging a number of departments on a line. This problem is known as single row Facility Layout. The problem is very difficult to be solved. In fact, it has as a particular case the linear ordering problem, which is strongly NP-hard. In this paper, a new mixed-integer linear programming model is proposed for the problem. Theoretical arguments as well as computational results are given which demonstrate the efficiency of the new model relatively to previous mixed-integer linear programming models proposed for the problem.
