Layout Design Problem Research Articles

An expert facility layout system: an object–oriented approach

A good layout design is important for a cellular manufacturing system (CMS) to operate efficiently. Traditional algorithms for layout design are confining and have limitations with regard to decision factors and knowledge representation. Knowledge–based expert systems have opened up a new way for modelling and evaluation of the ill–structured CMS layout problem. In addition to the advantages of integrating the vast amount of available knowledge and making it accessible to ordinary users, the knowledge–based approach is also useful for dealing with ambiguous, qualitative information and empirical knowledge that are often part of the CMS layout design process. The objective of this research is to develop a prototype for CMS Layout Design Expert System (CLADES) by using the expert system shell KEE (Knowledge Engineering Environment). This expert system would provide a powerful and eficient decision support tool for users in CMS layout design. CLADES solves the CMS layout problem in two stages. In the first stage, the machine cell layout is determined. In the second stage, the machine layout within each cell is determined. To obtain a reasonable layout design for a CMS, several factors which affect the decision are used as criteria in the CMS layout design problem. They are production quantity of the system, variation of part process routing, material handling system, unit load of an item, and dimensions of the floor plan. The design options considered by CLADES include three types of layout for machine cells, four types of layout for machines within a cell, and five types of material handling systems. In its current form, CLADES contains 58 rules, three models and three algorithms, and one algorithm is directly coded in CLADES in the LISP language. CLADES uses a tandem architecture, which connects the knowledge base to the model and algorithm base. This structure takes advantage of not only the expert system approach, but also the optimization approach. CLADES is coded using KEE/LISP in an object–oriented programming (OOP) fashion. It also has a user–friendly interface which makes the system easy to use. The object–oriented programming approach allows new rules, models and algorithms to be easily added to CLADES without changing the developed system structure. This built–in flexibility and convenience is very important for the modification and expansion of the system. This research has proved the feasibility of applying the knowledge–based approach to solve the CMS layout design problem. And the framework of CLADES shows it is a promising expert system to be developed into an industrial application.

Identifying Optimum Parameter Setting for Layout Design via Experimental Design and Analysis

The performance of finding an optimal solution is always a crucial engineering research topic. Quality of solutions obtained depends on the algorithm and its parameter settings applied to solve a problem. Machine layout design (MLD) problem involves the arrangement of machines into shop floor area to optimise performance measures. This paper presents the use of the experimental design and analysis to investigate the optimal parameter setting of Genetic Algorithm (GA) for designing multiple-row machine layout with demand uncertainty aiming to minimise the total cost. The analysis on the results obtained from computational experiments suggested that the proposed algorithm with and without adopting the optimised parameter setting performed distinctively on each problem size. The best GA parameters for MLD problem under stochastic customer demand were statistically compared and reported.

Layout problem of multi-component systems arising for improving maintainability

To improve the maintainability design efficiency and quality, a layout optimization method for maintainability of multi-component systems was proposed. The impact of the component layout design on system maintainability was analyzed, and the layout problem for maintainability was presented. It was formulated as an optimization problem, where maintainability, layout space and distance requirement were formulated as objective functions. A multi-objective particle swarm optimization algorithm, in which the constrained-domination relationship and the update strategy of the global best were simply modified, was then used to obtain Pareto optimal solutions for the maintainability layout design problem. Finally, application in oxygen generation system of a spacecraft was studied in detail to illustrate the effectiveness and usefulness of the proposed method. The results show that the concurrent maintainability design can be carried out during the layout design process by solving the layout optimization problem for maintainability.

Research on Optimization Technology of Facility Layout Based on Improved Differential Evolution Method

The facility layout design is the key problem in manufacturing system. Based on the constraints such as the cost of facility logistics and the space of equipment, this paper sets up a Quadratic Assignment Problem model of facility layout. The model is solved using Differential Evolution algorithm according to the features of facility layout, which is combined with Random Key technology. The test results performed on the liner and circular layout show the proposed approach can solve effectively the facility layout design problem.

An Integrated AHP-VIKOR Methodology for Facility Layout Design

A facility layout design (FLD) problem can be generally introduced as assignment of facilities (departments) to a site such that a set of criteria are satisfied or some objectives are minimized (maximized). Hence, it can be considered as a multi-criteria problem due to the presence of qualitative criteria such as maintenance or flexibility and quantitative criteria such as the total cost of handling material. The VIKOR method was developed to solve multiple criteria decision making problems with conflicting and non-commensurable (different units) criteria, assuming that compromising is acceptable for conflict resolution, the decision maker wants a solution that is the closest to the ideal, and the alternatives are evaluated according to all established criteria. This paper proposes a hierarchical analytic hierarchy process (AHP) and VIKOR approach to solve the FLD problem. A computer-aided layout-planning tool is adopted to generate the facility layout problems, as well as their quantitative data. The qualitative performance measures are weighted by AHP. VIKOR is then used to solve the FLD problem. Finally, the proposed integrated procedure is applied to three real-time examples.

A human–computer cooperative particle swarm optimization based immune algorithm for layout design

Packing and layout problems have wide applications in engineering practice. However, they belong to NP (non-deterministic polynomial)-complete problems. In this paper, we introduce human intelligence into the computational intelligent algorithms, namely particle swarm optimization (PSO) and immune algorithms (IA). A novel human–computer cooperative PSO-based immune algorithm (HCPSO-IA) is proposed, in which the initial population consists of the initial artificial individuals supplied by human and the initial algorithm individuals are generated by a chaotic strategy. Some new artificial individuals are introduced to replace the inferior individuals of the population. HCPSO-IA benefits by giving free rein to the talents of designers and computers, and contributes to solving complex layout design problems. The experimental results illustrate that the proposed algorithm is feasible and effective.

Concurrent cell formation and layout design using scatter search

Two key decisions in designing cellular manufacturing systems are cell formation and layout design problems. In the cell formation problem, machine groups and part families are determined while in the facility layout problem the location of each machine in each cell (intra-cell layout) and the location of each cell (inter-cell layout) are decided. Owing to the fact that there are interactions between two problems, cell formation and layout design problem must be tackled concurrently to design a productive manufacturing system. In this research, two problems are investigated concurrently. Some important and realistic factors such as inter-cell layout, intra-cell layout, operations sequence, part demands, batch size, number of cells, cell size, and variable process routings are incorporated in the problem. The problem is formulated as a mathematical model. Three different methods are described to solve the problem: multi-objective scatter search (MOSS), non-dominated genetic algorithm (NSGA-II), and the e-constraint method. The methods are employed to solve nine problems generated and adopted from the literature. Sensitivity analysis is accomplished on the parameters of the problem to investigate the effects of them on objective function values. The results show that the proposed MOSS algorithm performs better than NSGA-II and produces better solutions in comparison to multi-stage approaches.

Key techniques and applications of adaptive growth method for stiffener layout design of plates and shells

The application of the adaptive growth method is limited because several key techniques during the design process need manual intervention of designers. Key techniques of the method including the ground structure construction and seed selection are studied, so as to make it possible to improve the effectiveness and applicability of the adaptive growth method in stiffener layout design optimization of plates and shells. Three schemes of ground structures, which are comprised by different shell elements and beam elements, are proposed. It is found that the main stiffener layouts resulted from different ground structures are almost the same, but the ground structure comprised by 8-nodes shell elements and both 3-nodes and 2-nodes beam elements can result in clearest stiffener layout, and has good adaptability and low computational cost. An automatic seed selection approach is proposed, which is based on such selection rules that the seeds should be positioned on where the structural strain energy is great for the minimum compliance problem, and satisfy the dispersancy requirement. The adaptive growth method with the suggested key techniques is integrated into an ANSYS-based program, which provides a design tool for the stiffener layout design optimization of plates and shells. Typical design examples, including plate and shell structures to achieve minimum compliance and maximum bulking stability are illustrated. In addition, as a practical mechanical structural design example, the stiffener layout of an inlet structure for a large-scale electrostatic precipitator is also demonstrated. The design results show that the adaptive growth method integrated with the suggested key techniques can effectively and flexibly deal with stiffener layout design problem for plates and shells with complex geometrical shape and loading conditions to achieve various design objectives, thus it provides a new solution method for engineering structural topology design optimization.

A new approach for layout optimization in maintenance workshops with safety factors: The case of a gas transmission unit

In this study, an Integrated Simulation-Data Envelopment Analysis (DEA) approach is presented for optimum facility layout of maintenance workshop in a gas transmission unit. The process of repair of incoming parts includes various operations on different facilities. The layout problem in this system involves determining the optimum location of all maintenance shop facilities. Layout optimization plays a crucial role in this type of problems in terms of increasing the efficiency of main production line. Standard types of layouts including U, S, W, Z and straight lines are considered. First, the maintenance workshop is modeled with discrete-event-simulation. Time in system, average waiting time, average machine utilization, average availability of facilities, average queue length of facilities (AL) and average operator utilization are obtained from simulation as key performance indicators (KPIs) of DEA. Also, safety index and number of operators are considered as other KPIs. Finally, a unified non-radial Data Envelopment Analysis (DEA) is presented with respect to the stated KPIs to rank all layouts alternatives and to identify the best configuration. Principle Component Analysis (PCA) is used to validate and verify the results. Previous studies do not consider safety factor in layout design problems. This is the first study that presents an integrated approach for identification of optimum layout in a maintenance workshop of gas transmission unit by incorporating safety and conventional factors.

Cell formation and layout design with alternative routing: a multi-objective scatter search approach

Cellular manufacturing is a technology to improve the productivity and flexibility of manufacturing systems. Cell formation and layout design are two main problems in designing cellular manufacturing systems (CMSs). Due to the interaction between the two problems, these problems must be solved simultaneously to obtain the optimal solution. The problem is formulated as three different mathematical models which differ with respect to layout constraints and backward movements. A multi-objective scatter search is proposed to solve the integrated cell formation and layout design problem in CMSs. We introduce a new solution representation which is used in the algorithm. The performance of the algorithm is compared with the epsilon-constraint method and a well-known multi-objective evolutionary algorithm, non-dominated sorting genetic algorithm II (NSGA-II). The proposed algorithm not only obtained better solutions in comparison to the solutions proposed by past authors, but also it performs better than NSGA-II.

Design and optimisation for fixed area cellular layout problems using GA and SAA

This paper compares two familiar optimisation algorithms named Genetic Algorithm (GA) and Simulated Annealing Algorithm (SAA) to find out the best algorithm which is suitable for solving the cellular layout design problems. The objective is to minimise the movement of parts within the cell by appropriate placement of machines. In determining the physical location of work centres, some relative importance factors are considered. The priorities are given for the product, which has more volume and hazardous move and also to minimise back tracking move.

Multi-objective optimization in single-row layout design using a genetic algorithm

This paper presents the development of a genetic algorithm for determining a common linear machine sequence for multi-products with different operation sequences and facilities with a limited number of duplicate machine types available for a job. This work aims to minimize the total flow distance traveled by products, reduce the number of machines arranged in the final linear sequence, and decrease the total investment cost of the machines used in the final sequence. We assume that product flow runs only in the forward direction, either via in-sequence or bypass movement. We demonstrate the effectiveness of the proposed algorithm by solving a typical layout design problem taken from literature, and several randomly generated problems. Results indicate that the proposed algorithm serves as a practical decision support tool for resolving layout problems in manufacturing facilities.

A hybrid genetic algorithm for the single row layout problem

The arrangement of machines or departments along a straight line is known as single row layout and it is a widely employed configuration in flexible manufacturing systems. In this paper, a hybrid genetic algorithm (HGA) is proposed to solve the single row layout design problem with unequal sized machines and unequal clearances. The algorithm is developed by hybridisation of a genetic algorithm with a local search operator. The proposed HGA is tested on 51 well known data sets from the literature with equal and unequal clearances, and the results are compared with the best known solutions. Finally, algorithm's effectiveness in reaching previously known best solutions is revealed and improvements up to 7% in problems with unequal clearance are obtained.

An integrated AHP–NLP methodology for facility layout design

A facility layout design (FLD) problem can be generally introduced as assignment of facilities (departments) to a site such that a set of criteria are satisfied or some objectives are minimized (maximized). Hence, It can be considered as a multi-criteria problem due to presence of the qualitative criteria such as flexibility and the quantitative criteria such as total cost of handling material. This paper aims to incorporate qualitative criteria in addition to quantitative criteria for evaluating facility layout patterns (FLPs). We present a decision-making methodology based on a simple nonlinear programming model (NLP) and analytic hierarchy process (AHP). A computer-aided layout-planning tool, Spiral, is adopted to generate the FLPs, as well as their quantitative data. The AHP is then applied to determine weights of qualitative criteria. An NLP model is proposed to solve the FLD such that it considers both the quantitative and qualitative data simultaneously. Finally, the proposed integrated procedure is applied to a real example.

Multiple-attribute decision-making approach for an energy-efficient facility layout design

Due to the trends of energy shortage and energy price rise, energy efficiency, which was always ignored over the past decades, becomes a worldwide hot issue and also a significant challenge for most factories. Therefore, it is necessary to incorporate energy-relevant criterion as a key criterion with traditional criteria in the layout planning phase. As a multiattribute decision-making (MADM) problem, the evaluation and selection of facility layout alternatives are often difficult and time consuming since the criteria generally have different units and conflicting features. In this article, a MADM approach which incorporates the advantages of rough set theory, analytic hierarchy process (AHP), and technique for order preference by similarity to ideal solution (TOPSIS) is proposed to solve the facility layout design problem with considering both traditional layout criteria and energy relevant criteria. At first, rough set theory is integrated with AHP to determine the weights for each criterion of alternatives. Then, TOPSIS is applied to get the final alternative ranking. Besides, sensitivity analysis for both decision weights and production rates is performed, and a comparison among different decision-making approaches for the same problem is also studied to demonstrate the rationality of the final decision. Finally, a practical expanding case is studied to validate the proposed approach.

Weighted Euclidean distance based approach as a multiple attribute decision making method for plant or facility layout design selection

Article history: Received 25 November 2011 Accepted 11 January 2011 Available online 15 January 2012 In response to increasing inflexible customer demands and to improve the competitive advantage, industrial organizations have to adopt strategies to achieve cost reduction, continual quality improvement, increased customer service and on-time delivery performance. Selection of the most suitable plant or facility layout design for an organization is one among the most important strategic issues to fulfill all these above-mentioned objectives. Nowadays, many industrial organizations have come to realize the importance of proper selection of the plant or facility layout design to survive in the global competitive market. Selecting the proper layout design from a given set of candidate alternatives is a difficult task, as many potential qualitative and quantitative criteria need to be considered. This paper proposes a Euclidean distance based approach (WEDBA) as a multiple attribute decision making method to deal with the complex plant or facility layout design problems of the industrial environment. Three examples are included to illustrate the approach. © 2012 Growing Science Ltd. All rights reserved

A revised electromagnetism-like mechanism for layout design of reconfigurable manufacturing system

The layout design problem is one of the most important issues for manufacturing system design and control. A revised electromagnetism-like mechanism (REM) is proposed in this paper for the layout design of reconfigurable manufacturing systems utilizing automated guided vehicle. First, the formal model considering both loaded and empty flows is given. Then the REM is developed to solve the proposed model. In the REM, particles are encoded discretely. The charge of a particle is calculated according the total material handling cost of the particle. In the local search procedure, variable neighbourhood search strategy based on Hamming distance is adopted. In the moving procedure, the particles are moved according to the ordering of each element. To verify the effect of the proposed method, several computation cases are carried out. The computation results show that the proposed method is able to get optimal solutions for small scale problems and near optimal solutions within limited computation time for large scale problems. This indicates that the proposed method is effective and efficient.

A comparative analysis of meta-heuristic approaches for facility layout design problem: a case study for an elevator manufacturer

In this study, a facility layout problem having NP-hard problem characteristic is attempted to be solved by using two different meta-heuristic approaches--Genetic Algorithm (GA) and Simulated Annealing (SA)--and a hybrid approach--Genetic Algorithm/Simulated Annealing (HGASA). The case study is completed for a company which can be seen as a small or a medium size enterprise. First, parameter values of GA and SA are determined by testing for various combinations of them. Then, the algorithms are run for one hundred times. The results of the algorithms are compared based on their fitness values and calculation time requirements using the paired-t test, mean and standard values. The results show that SA performs better than the others in terms of the fitness values and the time requirements. In this study, we also test the performance of our GA, SA and HGASA methodologies using some of the well-known test problems from the literature. We obtain very close results to those in literature.

An integrated synthetic value of fuzzy judgments and nonlinear programming methodology for ranking the facility layout patterns

In this paper, the goal is to incorporate qualitative criteria in addition to quantitative criteria to facility layout design (FLD) problem. To this end, we present an integrated methodology based on the synthetic value of fuzzy judgments and nonlinear programming (SVFJ–NLP). The facility layout patterns (FLPs) together with their performance measures of total cost of material handling are generated by a computer-aided layout-design tool, CRAFT. Also, the performance measures of second quantitative criterion (construction cost of width walls) are calculated by appraising these FLPs. The SVFJ is then applied to collect the performance measures related to qualitative criteria and finally, a non-linear programming (NLP) model is proposed to solve the FLD. Results obtained from a real case study validate the effectiveness of the proposed model.

Optimal Layout Design for Agricultural Facility Using Simulated Annealing

(Keywords) combinatorial optimization problem, rational construction, simulated annealing, agricultural facility, optimal layout design Abstract In this study, optimal layout design approach was used to solve problems related to site layout design of agricultural facilities such as refrigeration house, grading and packing house and warehouse. A basic program to support the rational construction of such facilities using Simulated Annealing (SA), one heuristic algorithm and one solution for combinatorial optimization problems, was coded in C language (Satake(1999)). Layout design simulations were carried out to obtain information for the development of a program for solving practical problems. And, to clarify the feasibility of applying SA to the optimal layout design problems, the layout design simulation using the hill climbing (HC), which is another heuristic algorithm, was carried out for comparison with SA. As a result of the comparison with the optimum solution by HC, the value of cost evaluation by SA using exponential annealing was lower than that of hill climbing. Furthermore, in addition to this simulation, preliminary layout design simulation was also carried out to determine the applicability of the optimal layout design simulator to practical design. In this study, the layout design for a new building and parking was carried out. In the layout design, the site is not rectangular. As a result, the optimal design satisfying our condition was obtained.