JORSJ Vol. 50 No. 3 Abstract & Keywords 1. Inefficiency Evaluation with an Additive DEA Model under Imprecise Data, an Application on IAUK Departments Reza Kazemi Matin, Gholam@Reza Jahanshahloo, and Abdollah Hadi Vencheh abstract In imprecise data envelopment analysis (IDEA) (Cooper et al.~\cite{coop99}), the corresponding DEA models become non-linear and an important problem is to transform them into a linear programming one. In most of the current approaches to this problem, the number of decision variables increases dramatically, and usually the favorable results of these models are taken in several occasions. In this paper an additive DEA model is employed to evaluate the technical inefficiency of decision making units (DMUs) under imprecise data. The non-linear DEA model is transformed into an equivalent linear one, then the \emph{translation invariant} property is used and a \emph{one-stage} approach is introduced in this inefficiency evaluation. The approach rectifies the computational burden of previous methods in applications. keywords DEA, efficiency, additive model, imprecise data 2. A Multi-Stage Search Allocation Game with the Payoff of Detection Probability Ryusuke Hohzaki abstract This paper deals with a multi-stage two-person zero-sum game called the {\it multi-stage search allocation game} (MSSAG), in which a searcher and an evader participate. The searcher distributes his searching resources in a discrete search space to detect the evader, while the evader moves under an energy constraint to evade the searcher. At each stage of the search, the searcher is informed of the evader's position and his moving energy, and the evader knows the rest of the searcher's budget, by which the searcher allocates searching resources. A payoff of the game is the probability of detecting the evader during the search. There have been few search games that have dealt with the MSSAG. We formulate the problem as a dynamic programming problem. Then, we solve the game to obtain a closed form of equilibrium point, and to investigate the properties of the solution theoretically and numerically. keywords Search, game theory, nonlinear programming, dynamic programming 3. Multi-Item Production Planning and Management System Based on Unfulfilled Order Rate in Supply Chain Nobuyuki Ueno, Koji Okuhara, Hiroaki Ishii, Hiroaki Shibuki, and Toshiaki Kuramoto abstract In the automobile industry, a usual business model has a problem to realize mass customization, because it is difficult to satisfy the diversified customer needs. This paper proposes a multi-item production and inventory planning method of the mass customization with the consideration of the restriction of daily manufacturing capacity and so on. This model is formulated as a stochastic programming problem, and then the sub problem as a linear programming problem. An efficient and practical algorithm for the multi-item model is developed. keywords Inventory, production planning, mass-customization, mathematical programming, stochastic model 4. Electric Network Classifiers for Semi-Supervised Learning on Graphs Hiroshi Hirai, Kazuo Murota, and Masaki Rikitoku abstract We propose a new classifier, named {\em electric network classifiers}, for semi-supervised learning on graphs. Our classifier is based on nonlinear electric network theory and classifies data set with respect to the sign of electric potential. Close relationships to C-SVM and graph kernel methods are revealed. Unlike other graph kernel methods, our classifier does not require heavy kernel computations but obtains the potential directly using efficient network flow algorithms. Furthermore, with flexibility of its formulation, our classifier can incorporate various edge characteristics; influence of edge direction, unsymmetric dependence and so on. Therefore, our classifier has the potential to tackle large complex real world problems. Experimental results show that the performance is fairly good compared with the diffusion kernel and other standard methods. keywords Network flow, semi-supervised learning, SVM (support vector machine), graph kernel 5. A Switching Model of Dynamic Asset Selling Problem Mong-Shan Ee and Seizo Ikuta abstract This paper proposes an asset selling problem with a new selling strategy called the \emph{switching strategy} where multiple homogeneous assets on hand must be sold up to a specified deadline. At each point in time the seller is permitted to decide between 1) proposing a selling price up front to an appearing buyer and 2) concealing the price and letting the buyer come up with an offer. Our analysis indicates that under certain conditions there emerges a time threshold after which the seller switches from concealing his idea for the selling price to proposing this price, and vice versa. keywords Dynamic programming, posted price mechanism, reservation price mechanism 6. Locating Multiple Facilities in a Planar Competitive Environment Zvi Drezner, Atsuo Suzuki, and Tammy Drezner abstract We investigate the location of one or more facilities anywhere in an area in which several competing facilities already exist. The attractiveness of each facility is modeled by a utility function. Each customer selects the facility with the greatest utility function value. The objective is to find the locations for one or more facilities which attract the maximum buying power. We generate a set of candidate locations and solve the single facility problem by evaluating the buying power attracted to the new facility at each candidate location. We then solve the location of multiple facilities by converting the problem to a maximum covering problem. The solution procedure is illustrated on an example problem with 100 demand points and seven existing facilities. As a case study we find the best locations of new convenience stores in the city of Seto, Japan. keyword Facility planning, maximum covering problem, convenience stores 7. Quasiefficient Solutions of Multicriteria Location Problems with Rectilinear Norm in $\mathbb{R}^3$ Masamichi Kon abstract A multicriteria location problem with rectilinear norm in $\mathbb{R}^3$ and its quasiefficient solutions are considered. First, we give characterizations of its quasiefficient solutions by using optimal solutions of a minisum location problem and by using the concept of the summary diagram. Next, we propose the Frame Generating Algorithm to find all quasiefficient solutions of the multicriteria location problem. keywords Facility planning, location problem, multicriteria problem, rectilinear norm, quasiefficiency