Facility Layout Optimization Research Articles

An alternative multiple attribute decision making methodology for solving optimal facility layout design selection problems

In the present work, a systematic and an alternative multiple attribute decision making methodology is presented for selection of facility layout design selection problems. The proposed methodology is based on Preference selection index (PSI) method. In the proposed methodology appropriate facility layout design is selected for a given application without considering relative importance between facility layout design selection attributes. Two different types of facility layout design selection problems are examined to demonstrate, validate, and to check the reliability of proposed methodology. In addition, subjective cost benefit analysis is performed to study the benefits to cost to the company. Finally, the study has concluded that the facility layout design selection methodology based on PSI method is simple, logical, and more appropriate for solving the facility layout design selection problems.

A hybrid AI-based particle bee algorithm for facility layout optimization

Facility layout (FL) design presents a particularly interesting area of study because of its relatively high level of attention to aesthetics and usability qualities, in addition to common engineering objectives such as cost and performance. However, this generally presents a difficult combinatorial optimization problem for engineers. Swarm intelligence, an approach to decision making that integrates collective social behavior models such as the bee algorithm (BA) and particle swarm optimization (PSO), is being increasingly used to resolve various complex optimization problems. In order to integrate BA global search ability with the local search advantages of PSO, this study proposes a new optimization hybrid swarm algorithm—the particle bee algorithm (PBA) which imitates the intelligent swarming behavior of honeybees and birds. This study also proposes a neighborhood-windows technique for improving searching efficiency as well as a self-parameter-updating technique for preventing trapping into a local optimum in high-dimensional problems. This study compares PBA performance against BA and PSO performance in practical FL problem. Results show PBA performance is comparable to those of BA and PSO and can be efficiently employed to solve practical FL problem with high dimensionality.

Optimal layout of additional facilities for minimization of domino effects based on worst-case scenarios

Accidents involving domino effects are more serious than other type of accidents. Although there have been studies on such accidents, it is still difficult to examine the actual factors and causes since the domino effect is influenced nonlinearly by factors involving flame, overpressure, and flying objects. We considered the case of adding new facilities to an existing system in a given site. The layout of new facilities suggests positions that minimize the domino effects, based on nonlinear optimization taking domino factors into account. We quantitatively calculated the domino risk of each facility through the concept of combined domino factors (flame, overpressure, and missile). Also, we identified variations of domino damage extent of the target system through comparison of the impacts of domino effect when additional facilities were installed. Simulated annealing was adopted for searching optimal positions. As a case study, we applied the proposed method to the case of adding DME storage tanks in the existing LPG charging facilities. The presented framework of the quantitative assessment of domino risk and safety standard for the layout of additional facilities would be useful for proper layout design for improved accident prevention.

Comparison of Using Mixed-Integer Programming and Genetic Algorithms for Construction Site Facility Layout Planning

The use of modular construction has gained wide acceptance in the industry. For a specific construction facility layout problem such as site precast standardized modular units, it requires the establishment of an on-site precast yard. Arranging the precast facilities within a construction site presents real challenge to site management. This complex task is further augmented with the involvement of several resources and different transport costs. A genetic algorithm (GA) model was developed for the search of a near-optimal layout solution. Another approach using mixed-integer programming (MIP) has been developed to generate optimal facility layout. These two approaches are applied to solve with an example in this paper to demonstrate that the solution quality of MIP outperforms that of GA. Further, another scenario with additional location constraints can also be solved readily by MIP, which, however, if modeled by GA, the solution process would be complicated. The study has highlighted that MIP can perform better than GA in site facility layout problems in which the site facilities and locations can be represented by a set of integer variables.

Optimal facility layout under toxic release in process facilities: A stochastic approach

This paper presents a new approach for the optimal facility siting considering the uncertainty of toxic release in one of the installed facilities. The proposed formulation incorporates the effect of wind speed, wind direction and atmospheric stability to calculate the risk of death via probit functions and Monte Carlo simulation. The overall problem is initially modeled as a disjunctive program where the Cartesian coordinates of each new facility for siting and cost-related variables are the main unknowns to determine. Then, the convex hull approach is used to reformulate the problem as a mixed integer nonlinear program (MINLP). The numerical difficulties are shown in a case study where multiple optimal layouts have been found. In general, the numerical results demonstrate the potential of this approach to improve the process layout design activity.

Applying the sequence-pair representation to optimal facility layout designs

We present a new formulation for the facility layout problem based on the sequence-pair representation, which is used successfully in VLSI design. By tightening the structure of the problem with this formulation, we have extended the solvable solution space from problems with nine departments to problems with eleven departments.

Multi-Floor Facility Layout Optimization Using Slicing Tree Structure

This paper presents an algorithm for solving a multi-floor facility layout problem. The most apparent difference and also the potential difficulty in a multi-floor facility layout problem, compared to a single floor facility layout problem, are the problems regarding the placement of the vertical transportation equipments (elevators), which are to be used for vertical transportation occuring within the facility. Many solutions generated by algorithms presented for the multiple floor layout problems in the past had problems : irregular-shaped workshops and/or unnecessarily large unusable space (=dead space) within the facility. In this paper, we implement and improve Slicing Tree Structure for generating layout. Layout generated by using Slicing Tree Structure has a unique characteristic of making no dead spaces within the facility at all. We will present an algorithm, which generates near-optimal layout of workshops and elevators in a facility without dead space by improving the structure of Slicing Tree.

Enhanced Model Formulations for Optimal Facility Layout

This paper presents an improved mixed-integer programming (MIP) model and effective solution strategies for the facility layout problem and is motivated by the work of Meller et al. (1999). This class of problems seeks to determine a least-cost layout of departments having various size and area requirements within a rectangular building, and it is challenging even for small instances. The difficulty arises from the disjunctive constraints that prevent departmental overlaps and the nonlinear area constraints for each department, which existing models have failed to approximate with adequate accuracy. We develop several modeling and algorithmic enhancements that are demonstrated to produce more accurate solutions while also decreasing the solution effort required. We begin by deriving a novel polyhedral outer approximation scheme that can provide as accurate a representation of the area requirements as desired. We also design alternative methods for reducing problem symmetry, evaluate the performance of several classes of valid inequalities, explore the construction of partial convex hull representations for the disjunctive constraints, and investigate judicious branching variable selection priority schemes. The results indicate a substantial increase in the accuracy of the layout produced, while at the same time providing a dramatic reduction in computational effort. In particular, three previously unsolved test problems from the literature for which Meller et al.'s algorithm terminated prematurely after 24 cpu hours of computation (on a SUN Ultra 2 workstation with 390 MB RAM) with respective optimality gaps of 10.14%, 26.45%, and 40%, have been solved to exact optimality with reasonable effort using our proposed approach.

FACOPT: a user friendly FACility layout OPTimization system

The facility layout problem is a well-researched one. However, few effective and user friendly approaches have been proposed. Since it is an NP hard problem, various optimization approaches for small problems and heuristic approaches for the larger problems have been proposed. For the most part the more effective algorithms are not user friendly. On the other hand, user-friendly methods have not been effective in handling the intricacies such as unequal department sizes. In this research, we present FACOPT, a heuristic approach that is effective and user friendly. The software uses two methods, simulated annealing and genetic algorithm to solve the facility layout problem. Computational tests are also done to identify good parameter values and to compare the performance of the two algorithms. Scope and purpose Various methods have been proposed for facility layout where departments are laid out within a facility. However, many of them are not flexible enough to handle intricacies such as unequal department sizes. Others do not provide user-friendly interfaces. Thus, there is a need for user-friendly software incorporating effective and flexible procedures. In this research we present FACOPT, a heuristic approach that is effective and user friendly. The software uses two different approaches to solve the facility layout problem effectively. FACOPT has a Visual BASIC interface and runs under a Windows environment for ease of use.

An improved genetic algorithm for facility layout problems having inner structure walls and passages

This study proposes an improved genetic algorithm (GA) to derive solutions for facility layouts that are to have inner walls and passages. The proposed algorithm models the layout of facilities on gene structures. These gene structures consist of a four-segmented chromosome. Improved solutions are produced by employing genetic operations known as selection, crossover, inversion, mutation, and refinement of these genes for successive generations. All relationships between the facilities and passages are represented as an adjacency graph. The shortest path and distance between two facilities is calculated using Dijkstra's algorithm of graph theory. Comparative testing shows that the proposed algorithm performs better than other existing algorithms for the optimal facility layout design. Finally, the proposed algorithm is applied to ship compartment layout problems with the computational results compared with an actual ship compartment layout. Scope and purpose Facility layout problems (FLPs) concerning space layout optimization have been investigated in depth by researchers in many fields, such as industrial engineering, management science, and architecture, and various algorithms have been proposed to solve FLPs. However, these algorithms for the FLP cannot consider inner structure walls and passages within the block plan (or available area). They are also limited to a rectangular boundary shape of the block plan. Therefore, these algorithms could not be directly applied to problems having the curved boundary shape such as ship compartment layout, and an innovative algorithm which can treat such problems is needed. In this study, an improved genetic algorithm (GA) is proposed for solving problems having the inner structure walls and passages within an available area of a curved boundary. A comparative test of the proposed algorithm was performed to evaluate its efficiency. Finally, the proposed algorithm is applied to ship compartment layout problems with the computational results compared with an actual ship compartment layout. From the comparative test and the preliminary applications made to the ship's compartment layout, we demonstrate that the proposed algorithm has the ability to solve the FLPs having the inner structure walls and passages within the available area of the curved boundary.

Optimal Design and Layout of Industrial Facilities: An Application to Multipurpose Batch Plants

A mixed integer linear programming (MILP) formulation for the optimal design and layout of generic industrial facilities was proposed in part I of this work (see preceding paper). The applicability of the model is explored in this paper, through a study of the simultaneous design and layout of a batch multipurpose plants. Using as a basis the design model proposed by Barbosa-Póvoa and Macchietto (Comput. Chem. Eng. 1994, 18, 1013−1042), detailed design and layout aspects are studied in a single-level model. The resulting model determines simultaneously the optimal plant topology and layout over a two-dimensional space. In addition, the optimal plant operating conditions, such as schedule and resources consumption and production, are also obtained. Again, the problem is formulated as a mixed integer linear problem (MILP) in which binary variables are introduced to characterize operational and topological choices. The applicability of the proposed model is demonstrated through the solution of a set of representative examples.

Optimal Design and Layout of Industrial Facilities: A Simultaneous Approach

The design of industrial facilities is often dependent on the layout characteristics. Thus, a simultaneous approach to the design and layout of facilities is an important problem to be addressed. In this paper, the simultaneous design and layout of an industrial facility is studied, taking into account interactions that might be relevant when designing industrial facilities. The model developed here is essentially focused on the layout characteristics, whereas the design aspects are addressed more simply by considering the possible existence of a certain equipment item or connection. This is determined by adequate design models based on the specified industrial design characteristics (as will be explored in part II of this work; see following paper). The proposed model has therefore the particularity of being adjustable to alternative design problems. In this way, different operational and topological problem characteristics can be addressed, often dictated by the type of plant being designed (e.g., flow-...

Optimal 3D layout of industrial facilities

Facilities layout is concerned with the spatial arrangement of a set of departments or equipment items. This is an important stage at the design level, which often results in a complex problem due to the high number of decisions involved. A Mixed Integer Linear Programming (MILP) formulation, for the optimal layout of facilities within a two-dimensional (2D) continuous space has been developed (Barbosa-Póvoa et al . 2001). In this paper, the proposed model is extended to account for the location of equipment units within a 3D multi-floor continuous space. Different topological characteristics are considered such as equipment items orientation, distance restrictions, equipment connectivity inputs and outputs, rectangular and irregular equipment shapes, space availability and multifloor locations. In operational terms, production or operational sections are modelled as well as safety and operability restrictions. The final model is again described as a MILP where binary variables characterize topological choices and continuous variables describe the distances and locations involved. Finally, the applicability of the proposed formulation is shown through the resolution of a set of representative examples exploring the different model characteristics.

Hybrid Modelling for Optimal Facility Layout under Continuous Planning

Optimal facility layout design greatly reduces material handling cost, required floor area and dead space. The usual approaches do not consider material handling aspects and fail to provide an efficient manufacturing environment. This paper proposes a distinct methodology that integrates material handling equipment selection and facility layout design for a heavy manufacturing environment using knowledge-based and optimization technique. The algorithm was coded using C++ language. The applicability of the proposed hybrid methodology is simulated on a Pentium III, 550 MHz computer and applied to two projects involving 6 machines, 30 moves and 12 material handling equipment sets.

Optimal two-dimensional layout of industrial facilities

Layout is an important aspect of the design of industrial plants. In this paper a mathematical model is presented for the design of efficient and generic industrial layouts where a simultaneous solution of the block and detailed layout problem is considered. The optimal plant layout is obtained based on the minimization of the connectivity cost. Connectivity can describe simple pipe connections, guided vehicles or conveyors amongst others. Different topological characteristics are considered such as different equipment orientations, distance restrictions, non-overlapping constraints, different equipment connectivity inputs and outputs, irregular equipment shapes and space availability over a two-dimensional continuous area. In operational terms, production together with operational sections are modelled as well as safety and operability restrictions. A Mixed-Integer Linear Problem (MILP) is developed where binary variables are introduced to characterize topological choices and continuous variables describe the distances and locations involved. To conclude, the applicability of the proposed formulation is illustrated via a set of representative examples.

Fuzzy approach to the robust facility layout in uncertain production environments

The proposed method approaches the problem of the optimal facility layout using fuzzy theory. The optimal layout is a robust layout that minimizes the total material handling cost, when the product market demands are uncertain variables, which are defined as fuzzy numbers. Since each department has a limited production capacity, not all possible combinations, deriving from each product's market demand, are taken into account because some combination could exceed the overall department's productivity. Therefore, the optimal solution results by solving a 'constrained' fuzzy optimization problem, in which the fuzzy material handling costs corresponding to the layouts are evaluated, and a ranking method, which considers the grade of pessimism of the decision maker, is established to determine the optimal layout.

Facility layout optimization using simulation and genetic algorithms

Traditionally, the objective of a facility layout problem has been to minimize the material handling cost of the manufacturing system. While it is important to reduce the amount of material handling, the traditional methods do not address the actual time at which the material is transported. In today's short cycle time production environments, the timing of material movement may have a bigger impact on the productivity of the system than its cost. In this paper, a facility layout optimization technique is presented that takes into consideration the dynamic characteristics and operational constraints of the system as a whole, and is able to solve the facility layout design problem based on a system's performance measures, such as the cycle time and productivity. Each layout solution is presented in the form of a string that is suitable for analysis by a genetic algorithm technique. These solutions are then translated into simulation models by a specially designed automated simulation model generator. Genetic algorithms are used to optimize the layout for manufacturing effectiveness while simulation serves as a system performance evaluation tool. Combined with a statistical comparison technique to reduce the simulation burden, the test results demonstrate that the proposed approach overcomes the limitations of traditional layout optimization methods and is capable of finding optimal or near optimal solutions.

Optimal Facility Layout - A Generic Approach to Process Plants

This paper study the general facility layout problem is studied. A mathematical model is proposed and the optimal plant layout obtained based on the minimisation of the connectivity cost. In particular, the model considers different equipment orientations, distance restrictions, different equipment connectivity inputs and outputs, and space availability. Rectangular shapes, within a 2D plant continuous space, describe the equipment items. The problem is formulated as a Mixed Integer Linear Problem (MILP) where binary variables are introduced to characterise topological choices and continuous variables describe the distances and locations involved. The applicability of the proposed formulation is illustrated via a representative example.

Optimal facility layout design

The facility layout problem (FLP) is a fundamental optimization problem encountered in many manufacturing and service organizations. Montreuil introduced a mixed integer programming (MIP) model for FLP that has been used as the basis for several rounding heuristics. However, no further attempt has been made to solve this MIP optimally. In fact, though this MIP only has 2 n( n−1) 0–1 variables, it is very difficult to solve even for instances with n≈5 departments. In this paper we reformulate Montreuil’s model by redefining his binary variables and tightening the department area constraints. Based on the acyclic subgraph structure underlying our model, we propose some general classes of valid inequalities. Using these inequalities in a branch-and-bound algorithm, we have been able to moderately increase the range of solvable problems. We are, however, still unable to solve problems large enough to be of practical interest. The disjunctive constraint structure underlying our FLP model is common to several other ordering/arrangement problems; e.g., circuit layout design, multi-dimensional orthogonal packing and multiple resource constrained scheduling problems. Thus, a better understanding of the polyhedral structure of this difficult class of MIPs would be valuable for a number of applications.

マルコフ連鎖モデルと遺伝的アルゴリズムによる施設配置最適化

A new method is presented for optimization of facility layout. The pedestrian flow is modeled by using Markov chains, where the distribution of existence probability in the stationary state is calculated by solving an eigenvalue problem. In the proposed method, the pedestrian distribution in the path between every pair of the facilities is first considered, and the large generator matrix is condensed to a small one before carrying out the eigenvalue analysis to find the stationary state. A genetic algorithm (GA) is used for optimization, and a hybrid GA is presented for simultaneously optimizing the assignment and the locations of the facilities. In the examples, characteristics of the distribution of the utilities of the facitilies are discussed.