In this paper, a municipal decision support methodology is proposed to evaluate the location of refuse incineration plant to dispose the municipal waste using the model of descriptive extension of Analytic Hierarchy Process, called D-AHP. In this model, the rank reversal phenomena are legitimately observed and explanatory. The alternative sites of the refuse incineration plant are located in a hypothetical city, and the alternatives are evaluated. The results of the evaluation show that D-AHP is useful for the case when the number of alternatives such as the number of sites of the refuse incineration plant may change.

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In this paper. taking account of the detectability of a sensor for a target being in the neighbor-hood of a searching point, an optimal distribution of searching effort maximizing detection probability for a stationary target is investigated. Defining a function of extended effect of searching effort, the problem is formulated as a variational problem and theorems of the optimal distribution of searching effort are derived. By this model, the assumption of local effectiveness for searching effort in Koopman's model is removed and reality of the model is improved. A procedure for calculating the optimal (or suboptimal) solution is presented. and applying , an optimal search plan for the datum search situation is analyzed in detail. Meaning of the conditions of the optimal solution and its properties are elucidated. Generalizations of the model and problems to be investigated in future are also discussed.

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In this paper, we investigated mathematical models on reservoir operation problem and provided a fuzzy model based on Markov chain time series for Karkheh dam in Iran. Based on fuzzy partitioning of monthly stream flows, calculated by time series, a Markovian forecasting model was developed. A deterministic and a fuzzy partitioning stochastic dynamic programming model were formulated for the problem. The goals were formulated with weighting priorities and the optimal reservoir operation was determined. Using historical data, the performance of the dam was simulated. Results of this simulation clearly showed that the fuzzy partitioning proposed stochastic model outperforms the deterministic model.

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Given a simple graph G with a vertex set. V and a set. of "requirements" {r_<vw>|v,w∈V}, we consider a problem to find a Hamilton cycle minimizing an objective function similar to that in the optimum requirement spanning tree (ORST) problem studied by Hu. And we show that a particular Hamilton cycle C^* which is explicitly definable is a solution to the problem when G is complete and {r_<vw>} satisfies inverse Supnick property closely related to Monge property. It is of great interest that C^* is also a solution to the symmetric traveling salesman problem with (not inverse) Supnick property. The result in this paper can be applied to the construction of ring networks with high reliability in case where the inverse Supnick property is naturally assumed.

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In this study, we introduce the differential equation model which can explain some hierarchical growth processes. This model is based on the assumptions that some growth processes can be devided into plural stages, and that in a given stage, increasing speed of population (human or otherwise) depends on the size of population in the previous stage. For example, urbanization process can be devided into residential land development stage and building up stage, and the expanding speed of the built-up area depends on the residential development area. In accordance with these assumptions, we formulate the simultaneous differential equations, then calculate their general solutions. We consider that this model can describe the sales of the video game machines, because the process of buying them has following two stages, first a person wants to buy the machine, then he actually buys it. In addition, the person who gets the game machine will buy some video game softwares. Deriving new model with these thought, we can confirm that the model can explain the sales of video game machines well especially shortly after the machine's being put on the market. This consequence indicates that the hierarchical model is appropriate for the explanation of the growth tendency of the beginning period. Furthermore, the application of this model to explain the sudden growth in a growth process is proposed in this paper. When a price reduce campaign is launched, the sales of the machines shows a tendency of sudden increase. The model can explain this change by adding only two parameters to the original model. Our model has so simple structure that it will be able to represent some underlying mechanisms of various growth processes.

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An interesting combinatorial (enumeration) problem arises in the initial phase of the polyhedral homotopy continuation method for computing all solutions of a polynomial equation system in complex variables. It is formulated as a problem of finding all solutions of a specially structured system of linear inequalities with a certain additional combinatorial condition. This paper presents a computational method for the problem fully utilizing the duality theory and the simplex method for linear programs, and report numerical results on a single cpu implementation and a parallel cpu implementation of the method.

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To achieve the optimal control of material removal rate (MRR) for a machining project, a Dynamic Machining Project Control (DMPC) Model is proposed under the considerations of order quantity and deadline constraints. This paper not only introduces material removal rate into the objective function dynamically, but also implements Calculus of Variations to resolve the continuous control problem comprehensively. In addition, the optimal solution to minimize the cost of a machining project with production deadline is provided, and the decision criteria for selecting the optimal solution are recommended. Moreover, the sensitivity analyses of decision variables in the optimal solution as well as the numerical simulation of a real industrial problem are fully discussed. This study contributes a significant approach to control a machining project for production engineers in today's machining industry with profound insight.

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This paper deals with a search game. In a search space, a target wants to avoid a searcher by selecting his path. The searcher has superior mobility and makes effort to detect the target by distributing divisible searching effort anywhere he wants. The target might move diffusively from the starting points but his motion is restricted by some constraints on his maximum speed and energy consumption. The searcher also has limits on the total amount of searching effort. A payoff of the game is assumed to be the detection probability of the target, which is represented by an exponential function of the cumulative searching effort weighted by the probability distribution of the target. Regardless of the payoff function, we name the game the search allocation game with energy constraints. We formulate it as a two-person zero-sum game and propose a linear programming method to solve it. Our formulation and method have the flexibility to be applied to other search models by a small modification.

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