Irohara Takashi

It is generally known that the facility layout problem (FLP) is to find an optimal layout with respect to the minimization of material handling costs (MHC) between departments. In most studies on FLP, the existence of aisles and I/O locations in each department are ignored. While there are some layout techniques that consider the aisle structure and I/O location, they have many problems. There are not any techniques that consider the I/O type of a department. Additionally in most studies, the FLP is modeled as a combinatorial optimization problem. When solving a FLP model, only the relative location of departments, aisles and I/O can be decided, not a detailed layout. In this paper, a new layout design methodology is proposed, in which a detailed layout including the aisle structure and I/O locations of departments can be decided using the hybrid approach of combinatorial optimization and mathematical programming approaches. In addition, a new layout expression is proposed based on a revised location matrix that enables one to consider not only the guillotine-cut type layout but also the spiral type layout. The proposed algorithm is based on Simulated Annealing combined with some local search. The objective function is the minimization of materials handling cost between the I/O points of departments along the aisle with the shortest distance. The results of computational experiments show the effectiveness of the proposed algorithm.

In this paper, a new layout expression based on the location matrix and some heuristics are proposed for the determination of aisle structure and I/O locations of each department in a facility layout problem. The proposed genetic algorithm-based algorithm finds multiple solutions along the Pareto optimal frontier. The objective here is to minimize (1) material handling cost and (2) building area. The material movements assume that they are transferred along the shortest distance aisle between the I/O locations of those departments. The results of computational experiments show the effectiveness of the proposed algorithm.

The design of the physical layout is the most important issue to be considered in the early stages of manufacturing system design. Operating costs and system efficiency are significantly affected by material handling. Generally, the facility layout problem is to find an optimal layout with respect to minimizing material handling costs between departments. In most existing studies on the problem, the distance between departments is assumed to be the rectilinear distance between the centers of the departments. Those approaches ignore the existence of aisle and I/O points in each department. A new design methodology for the facility layout problem is presented in this paper. Our objective is to minimize the penalty for the redundant aisle areas and irregular shapes of departments, besides material handling costs. The material movements assume that they are transferred along the shortest aisles between the I/O points of those departments. In this paper, a new layout expression based on location matrix and some heuristics are proposed for determining aisle structure and I/O points. In the new layout expression, the I/O points of each department are located according to intradepartment material flows. We develop an improvement-type layout algorithm based on simulated annealing. In this paper, we propose a new design methodology for the facility layout problem that considers the aisle structure and I/O points of each department. There are three types of I/O points (U, L and I type) and they are decided to minimize the objective while maintaining access to the aisle. Experimental results show that our approach performs quite well for the minimization of material handling costs and the aisle areas.

We propose a new framework of facility layout problems which takes the production efficiency into account explicitly. In the classical framework of facility layout problems, layouts are evaluated only by the material handling cost, and any aspects as to how layouts affect the production efficiencies are not considered. In real systems, however, the layout of facilities do affect the production efficiencies such as throughput, lead time and so on. Thus, in general, there should exist the "best" layout which absorbs the variability involved in the system and attains the highest production efficiency. In short, our problem is to find the layout of facilities which results in the maximal production efficiency. We refer this type of layout problems as the "Stochastic Facility Layout Problem (SFLP)". In this paper, we present an example of SFLP which finds an optimal combination of the facility layout and the buffer space allocation to achieve the maximal throughput. In case when the physical size of a buffer space can not be ignored compared with the facility itself, allocating buffer spaces to a facility affects the distances between facilities. In such a case, the production efficiency (throughput, say) depends on both buffer space allocation and facility layout in a complex way. Our problem gives rational solutions for such a situation. Through this example problem, we discuss the merits and the demerits of SFLP compared with the classical facility layout problems.

In this paper, we address the problem of cellular manufacturing system, which, in essence, consists of three main problems, cell formation and machine duplication and part subcontract. While a number of research have been conducted on the problem, most of them considered machine duplication and part subcontract separately. One paper considering cell formation, machine duplication and part subcontract is published, but the paper proposes two step method, so has a problem for possibility of local search. On the contrary this paper propose an integrated approach using Genetic Algorithm (GA) to solve the problems simultaneously on one step method. Our numerical experiments and results show that our method performs better compared to a conventional method which using two step method. © 2001, The Japan Society of Mechanical Engineers. All rights reserved.

At present, it is important problem to reduce transportation cost for most of corporation. In recently, most of customer have specifying time to be served by transportation companies, and it is important for the companies to keep it. Because both reducing cost and improving quality of services are hoped by many transportation companies. Thus, one of the best ways to keep the time window is better scheduling of trucks. And useless waiting time and running time can be reduced. But these are made difficult by following two things. 1 : Time window of customers. 2 : Limited number of berths. Particularly in case of multi route service, 2 is very important. And it is very difficult to solve VRP under limited number of berths. So how to make schedules including both 1 and 2 is needed very much. But there is no research until now. Moreover by making these, it can be easy to work at depot. For these reasons, in this research I develop how to solve Vehicle Routing Scheduling Problem under Limited Number of Berths. © 2001, The Japan Society of Mechanical Engineers. All rights reserved.

This paper presents an algorithm to get a solution of the facility layout problem for multiple-floors. In a number of previous research, these problems are formulated as a combinatorial optimization problem to minimize only the cost owing to material flow between departments ignoring the utilization of the elevators, which is a typical transportation equipment for vertical transportation. In our proposed algorithm, the capacity of elevators is taken into consideration, Then the proposed algorithm optimizes the number and location of elevator with the consideration of the assignment of each carriage to the elevators. Numeric results are given to demonstrate the effectiveness of the proposed algorithm. (C) 1999 Elsevier Science Ltd. All rights reserved.

The facility layout problem can be formulated as a combinatorial optimization problem to minimize the total cost owing to material flow. Most of the paper is focusing on such a layout problem in two-dimensions. However it would be better to treat the layout problem in three-dimension (3 D) in order to minimize the distance between equipment and the land area. For bin-packing problem, there are some papers in 3 D, but in those model flow between bin is not considered. That’s why this paper proposed a 3 D-layout technique for unequal shape and area departments. Computational experiments are suggesting that proposed algorithm will produce better solution than plain layout which is the result of previous algorithm. © 1999, The Japan Society of Mechanical Engineers. All rights reserved.

In this paper, a new type of Vehicle Routing Problem in which distribution centers exist between factories and customers, is addressed. Each distribution center has no fixed category, which means all customers can be served from any distribution center. When demands occur, products are transported from factories to distribution centers by large fleets, and distributed to customers by small fleets. This results in an inter-dependent relationship between transportation and distribution. However, to take into consideration both transportation from factories to distribution centers and distribution from distribution centers to customers, the solution space becomes extremely large. Thus, it is utterly impracticable to solve the problem by using optimization. This paper, therefore, proposes an integrated heuristic using Tabu Search and Simulated Annealing with two-phase approaches to solve the problem. Numerical experiments has been carried out to demonstrate an effectiveness of the proposed technique.

In this paper, we proposed a hybrid genetic algorithm (Hybrid GA) approach to a multi-objective vehicle routing problem (MVRP). The objective functions considered in this MVRP are (1). to minimize the number of vehicles used, (2). to minimize the total traveling distance for vehicles, (3). to minimize the total waiting time for vehicles, and (4). to maximize the grade of customer satisfaction with due-time. With respect to customer satisfaction with due-time, we used the concept of fuzzy due-time because it can describe customers' preference with service time better than crisped expression of satisfaction with 0 and 1. To handle such multi-objectivity, a set of Pareto optimal solutions are searched by Hybrid GA. Among Pareto optimal solutions, we furthermore targeted at compromise solutions whose objective functions take almost intermediate values each, in order to produce realistic routing plans for vehicles. In the proposed algorithm, a local search procedure is applied to each solution at each generation for efficient search of solutions. The computational results show that the proposed algorithm is efficient for solving MVRP.

In this paper, we address the issue of a cellular munufacturing system layout design, which, in essence, consists of two main problems, cell formation and cell layout, While a number of studies have been conducted on this issue, the two problems were usually considered sequentially, and the impact of cell layout was ignored when solving cell formation. Moreover, it was often assumed that all cells are equal in area and shape, which is not practical for industry-scaled problems. We propose an integrated approach using the Genetic Algorithm (GA) to solve the problems simultaneously, with an assumption that not all cell areas and shapes are equal. Our numerical experiments and results show that our method performs better compared to a conventional method in which cell formation and cell layout are considered sequentially.

Automated Guided Vehicle systems (AGVs) are important in modern manufacturing systems. One of the important issues in the design of AGVs is to determine the direction of AGV, which is known as AGV flow path design problem. Though a number of significant research has been conducted on this problem, most of them do not take into consideration the effect of machine layout when designing AGV flow path. In this paper, an integrated technique employing Genetic Algorithm (GA) and Simulated Annealing (SA) to solve AGV flow path design problem is proposed. GA is used to search for AGV flow path direction, while SA is simultaneously used to search for machine layout.

In the previous paper, a layout technique (CARD-SA) to solve the large size facility layout problem was proposed. In this paper, the CARD-SA is applied to the refinery and petrochemical plant problem. The stock and flow data of the problem is same with the existing plant data, and several realistic constraints are considered. The number of equipment to assign is over 100,and the difference of each equipment size is very large. The objective function is to minimize the total length of pipe to connect the equipment. Numerical tests are suggesting, the CARD-SA is effective to solve the problem.

In this paper, a layout technique for unequal area and shape departments with a main aisle is proposed. In this technique, layout is represented by the flexible aisle structure (FAS),which is an improvement on the flexible bay structure (FBS), by considering the main aisle inside the building. FBS and FAS treat unequal area and unfixed rectangular shape departments. By using FAS, assignments of departments and aisle structure are optimized simultaneously during the search. In the objective function, which is based on the material handling cost between departments, we use the distance between departments along aisles, in order to take into account the existence of the main aisle. Also, a new measurement for evaluating department shapes, which have unequal area, unfixed rectangles, is proposed. Experimental results indicate the effectiveness of controlling department shapes by this new measurement and of using distance along aisles in the objective function.

Recently, due to consumer demands have been varied, it is essential that a facility layout is able to adapt to the demands dynamically. In this paper, we present a technique to solve a dynamic layout problem. We deal with the problem by simulataneously considering two kinds of flexibility. One is involved with the rearrangement and the changing size of departments. The other is for the fixed area and shape of the building. The Bottom-Left (BL) algorithm is integrated in the technique in order to treat rectangular departments. The two steps Geretic Algorithm (GA) to improve the solutions, which involved an operation called GENITOR algorithm, is proposed. Numerical experiments are carried out to demonstrate the effectiveness of the proposed technique.

The facility layout problem can be formulated as a combinatorial optimization problem to minimize the total cost owing to material flow. It is impossible to apply optimal method to the problem because of calculation time. Then, sub-optimal method (CARD-SA) using Simulated Annealing for optimization was proposed. However, it is quite difficult to apply CARD-SA to the large size problem like the number of department is over 100. For this reason, we improve the CARD-SA to increase the number of department and to extend the variety of the department shape. Computational experiments suggest that this algorithm is quite effective.

This paper presents a technique to solve the facility layout problem with rectangular departments of unequal areas. This problem can be formulated as a combinatorial optimization problem to minimize the total cost owing to material flow between departments. It is, however, computationally timeconsuming to find optimal solutions for large problems, because they are highly combinatorial in nature. Furthermore, these problems exhibit many local minim. These properties make them suitable candidates for the application of simulated annealing, which is a stochastic optimization procedure. A suboptimal method is then developed, which is a new improvement-type technique based on simulated annealing. In this technique, a new algorithm for updating placement of departments is proposed. This algorithm enables the application of simulated annealing to solve the problems considered here. This technique also offers increased flexibility to the optimization process, making the solution much less dependent upon the initial layout. Numerical results are given to demonstrate the effectiveness of the presented technique.