Yoshio Uemura

Interactive fuzzy programming for multi-level linear programming problems with fuzzy parameters

This paper presents interactive fuzzy programming for multi-level linear programming problems with fuzzy parameters. In fuzzy programming for multi-level linear programming problems, recently developed by Lai et al., since the fuzzy goals are determined for both an objective function and decision variables at the upper level, undesirable solutions are produced when these fuzzy goals are inconsistent. In order to overcome such problems, after eliminating the fuzzy goals for decision variables, interactive fuzzy programming for multi-level linear programming problems with fuzzy parameters is presented. In our interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating the satisfactory degrees of decision makers with considerations of overall satisfactory balance among all levels. Illustrative numerical examples for two-level and three-level linear programming problems are provided to demonstrate the feasibility of the proposed method.

Fuzzy programming and profit and cost allocation for a production and transportation problem

Abstract In this paper, we deal with a real problem on production and transportation in a housing material manufacturer, and consider a production and transportation planning under the assumption that the manufacturer makes multiple products at factories in multiple regions and the products are in demand in each of the regions. First, we formulate mixed zero–one programming problems such that the cost of production and transportation is minimized subject to capacities of factories and demands of regions. Second, to realize stable production and satisfactory supply of the products in fuzzy environments, fuzzy programming for the production and transportation problem is incorporated. Finally, under the optimal planning of production and transportation, we show a profit and cost allocation by applying a solution concept from game theory. Using actual data, we show usefulness of the fuzzy programming and a rational allocation scheme of the profit and cost.

Interactive fuzzy programming for two-level linear and linear fractional production and assignment problems: A case study

Abstract In this paper, we deal with actual problems on production and work force assignment in a housing material manufacturer and a subcontract firm. We formulate two kinds of two-level programming problems: one is a profit maximization problem of both the housing material manufacturer and the subcontract firm, and the other is a profitability maximization problem of them. Applying the interactive fuzzy programming for two-level linear and linear fractional programming problems, we derive satisfactory solutions to the problems. After comparing the two problems, we discuss the results of the applications and examine actual planning of the production and the work force assignment of the two firms to be implemented.

A decentralized two-level transportation problem in a housing material manufacturer: Interactive fuzzy programming approach

Abstract In this paper, we deal with a transportation problem in a housing material manufacturer and derive a satisfactory solution to the problem by taking into account not only the degree of satisfaction with respect to objectives of the housing material manufacturer but also those of two forwarding agents to which the housing material manufacturer entrusts transportation of products. The two forwarding agents handle the regular transportation and the small lot transportation, and each of them assigns work force, the transformation tasks properly. There are two objectives in the housing material manufacturer: one is to minimize the transportation cost and the other is to minimize the opportunity loss with respect to transportation time. The objectives of the two forwarding agents are to maximize their profits. We formulate the transportation planning and work force assignment problem as a decentralized two-level integer programming problem, and derive a satisfactory solution by applying an interactive fuzzy programming method.

Manpower allocation using genetic annealing

In this paper, we focus on a real size manpower allocation problem. It was modeled after a real world problem of distributing the salesmen force over the branches of a company. The problem includes multiple objectives and the number of salesmen at each branch is unspecified. Conventional integer programming approach and conventional metaheuristics seem to have problems with solving the large size version of this problem. The versatility of our proposed heuristics based on a modification of genetic annealing is exemplified through solving the real size manpower allocation problem. For comparison sake, several small sized versions were solved using our method, conventional integer programming approach, and some well known metaheuristics.

Interactive fuzzy programming for two‐level nonconvex nonlinear programming problems through genetic algorithms

In this paper, we present interactive fuzzy programming through genetic algorithms, which are reported their effectiveness to solving nonconvex nonlinear programming problems, for multi-level nonconvex nonlinear programming problems. In the proposed method, fuzzy goals for objective function of each decision maker and a ratio of satisfactory degrees of decision makers at adjacent two levels are introduced to take the vague or fuzzy nature of human judgments into account, and mathematical programming problems for obtaining satisfactory solutions concerned in some groups within all the decision makers are successively solved to lead to a global satisfactory solution such that the decision makers at relatively upper levels are esteemed and the satisfactory degree of each decision maker balances with those of the others. Finally, a numerical example is given to illustrate an interactive process in the proposed method for deriving a satisfactory solution.

Interactive fuzzy programming for multi-level linear programs with fuzzy numbers

In the fuzzy programming for multi-level linear programming problems developed by Lai et al. (1996), since the fuzzy goals are determined for both an objective function and decision variables at the upper level, undesirable solutions are produced when these fuzzy goals are inconsistent. In order to overcome such problems, after eliminating the fuzzy goals for decision variables, interactive fuzzy programming for multi-level linear programming problems with fuzzy parameters is presented. In our interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating the satisfactory degrees of decision makers at the upper level with considerations of overall satisfactory balance among all levels. An illustrative numerical example for three-level linear programming problems is provided to demonstrate the feasibility of the proposed method.