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 nonlinear 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 nonlinear DEA model is
transformed into an equivalent linear one, then the \emph{translation
invariant} property is used and a \emph{onestage} 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 MultiStage
Search Allocation Game with the Payoff of Detection Probability
Ryusuke Hohzaki

abstract

This paper deals with a multistage
twoperson zerosum game called the {\it multistage 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. MultiItem
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 multiitem 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
multiitem model is developed. 
keywords 
Inventory, production planning, masscustomization,
mathematical programming, stochastic model 
4. Electric Network Classifiers for SemiSupervised Learning on Graphs
Hiroshi Hirai, Kazuo Murota, and Masaki
Rikitoku

abstract 
We propose a new classifier, named
{\em electric network classifiers}, for semisupervised 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 CSVM 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, semisupervised
learning, SVM (support vector machine), graph kernel 
5. A Switching Model of Dynamic
Asset Selling Problem
MongShan 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 