Mutsunori Banbara

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In this paper, we propose a new method to encode Constraint Satisfaction Problems (CSP) and Constraint Optimization Problems (COP) with integer linear constraints into Boolean Satisfiability Testing Problems (SAT). The encoding method (named order encoding) is basically the same as the one used to encode Job-Shop Scheduling Problems by Crawford and Baker.(More)
We present the Prolog Cafe system that translates Prolog into Java via the WAM. Prolog Cafe provides multi-threaded Prolog engines. A Prolog Cafe thread seem to be conceptually an independent Prolog evaluator and communicates with each other through shared Java objects. Prolog Cafe also has the advantages of portability, extensibility, smooth interoperation(More)
There have been several proposals for logic programming language based on linear logic: Lolli [8], Lygon [7], LO [3], LinLog [2], Forum [11], HACL [10]. In these languages, it is possible to create and consume resources dynamically as logical formulas. The efficient handling of resource formulas is, therefore, an important issue in the implementation of(More)
Extended Abstract A (finite) Constraint Satisfaction Problem (CSP) is a combinatorial problem to find an assignment which satisfies all given constraints over finite domains. A SAT-based CSP solver is a program which solves a CSP by encoding it to SAT and searching solutions by SAT solvers. Remarkable improvements in the efficiency of SAT solvers make(More)
The effective use of ASP solvers is essential for enhancing efficiency and scalability. The incidence matrix is a simple representation used in Constraint Programming (CP) and Integer Linear Programming for modeling combinatorial problems. Generating test cases for event-sequence testing is to find a sequence covering array (SCA). In this paper, we consider(More)
We propose a satisfiability testing (SAT) based exact approach for solving the two-dimensional strip packing problem (2SPP). In this problem, we are given a set of rectangles and one large rectangle called a strip. The goal of the problem is to pack all rectangles without overlap, into the strip by minimizing the overall height of the packing. We show the(More)