Takehide Soh

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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)
In this paper, we propose a new approach, called lemma-reusing, for accelerating SAT based planning and scheduling. Generally, SAT based approaches generate a sequence of SAT problems which become larger and larger. A SAT solver needs to solve the problems until it encounters a satisfiable SAT problem. Many state-of-the-art SAT solvers learn lemmas called(More)
The course timetabling problem can be generally defined as the task of assigning a number of lectures to a limited set of timeslots and rooms, subject to a given set of hard and soft constraints. The modeling language for course timetabling is required to be expressive enough to specify a wide variety of soft constraints and objective functions.(More)
This paper presents a SAT-based pseudo-Boolean (PB for short) solver named PBSugar. PBSugar translates a PB instance to a SAT instance by using the order encoding, andsearches its solution by using an external SAT solver, such as Glucose. We first introduce an optimized version of the order encoding, and it is appliedto encode each PB constraint(More)
Encoding finite linear CSPs as Boolean formulas and solving them by using modern SAT solvers has proven to be highly effective, as exemplified by the award-winning sugar system. We here develop an alternative approach based on ASP. This allows us to use first-order encodings providing us with a high degree of flexibility for easy experimentation with(More)
This paper proposes a new hybrid encoding of finite linear CSP to SAT integrating order and log encodings. The former maintains bound consistency by unit propagation and works well for instances with small/middle domain sized variables and/or arity of constraints. The latter generates smaller CNF and is suitable for instances with larger domain sized(More)