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Hiroki Yanagisawa – One of the best experts on this subject based on the ideXlab platform.
improved approximation bounds for the student project Allocation Problem with preferences over projectsJournal of Discrete Algorithms, 2012Co-Authors: Kazuo Iwama, Shuichi Miyazaki, Hiroki YanagisawaAbstract:
Manlove and O@?Malley (2008)  proposed the Student-Project Allocation Problem with Preferences over Projects (SPA-P). They proved that the Problem of finding a maximum stable matching in SPA-P is APX-hard and gave a polynomial-time 2-approximation algorithm. In this paper, we give an improved upper bound of 1.5 and a lower bound of 21/19 (>1.1052).
Marco Caserta – One of the best experts on this subject based on the ideXlab platform.
an exact algorithm for the reliability redundancy Allocation ProblemEuropean Journal of Operational Research, 2015Co-Authors: Marco CasertaAbstract:
The redundancy Allocation Problem is the Problem of finding an optimal Allocation of redundant components subject to a set of resource constraints. The Problem studied in this paper refers to a series-parallel system configuration and allows for component mixing. We propose a new modeling/solution approach, in which the Problem is transformed into a multiple choice knapsack Problem and solved to optimality via a branch and cut algorithm. The algorithm is tested on well-known sets of benchmark instances. All instances have been solved to optimality in milliseconds or very few seconds on a normal workstation.
Andrew Lim – One of the best experts on this subject based on the ideXlab platform.
a stochastic beam search for the berth Allocation ProblemDecision Support Systems, 2007Co-Authors: Fan Wang, Andrew LimAbstract:
In this paper, the optimization of the Berth Allocation Problem (BAP) is transformed into a multiple stage decision making procedure and a new multiple stage search method, namely stochastic beam search algorithm, is proposed to solve it. New techniques such as an improved beam search scheme, a two-phase node goodness estimation, and a stochastic node selection criteria are proposed. Real-life information provided by Singapore Port was collected as our test data. Experimental results show that the proposed stochastic beam search is more accurate and efficient than both the state-of-the-art meta-heuristic and the traditional determinist beam search.
GECCO – The general yard Allocation ProblemGenetic and Evolutionary Computation — GECCO 2003, 2003Co-Authors: Ping Chen, Andrew Lim, Brian RodriguesAbstract:
The General Yard Allocation Problem (GYAP) is a resource Allocation Problem faced by the Port of Singapore Authority. Here, space Allocation for cargo is minimized for all incoming requests for space required in the yard within time intervals. The GYAP is NP-hard for which we propose several heuristic algorithms, including Tabu Search, Simulated Annealing, Genetic Algorithms and the recently emerged “Squeaky Wheel” Optimization (SWO). Extensive experiments give solutions to the Problem while comparisons among approaches developed show that the Genetic Algorithm method gives best results.
AAAI/IAAI – The yard Allocation Problem, 2002Co-Authors: Ping Chen, Andrew LimAbstract:
The Yard Allocation Problem (YAP) is a real-life resource Allocation Problem faced by the Port of Singapore Authority (PSA). We first show that YAP is NP-Hard. As the Problem is NP-Hard, we propose several heuristics, including Tabu Search methods with short and long term memory, a “Squeaky Wheel” Optimization (SWO) method, and a new hybrid which combines SWO with TS to solve the Problem. Extensive experiments show very favorable results for our new hybrid method.