Abstract. In this paper, the optimization of the Berth Allocation Problem (BAP) is transformed into a multiple stage decision making procedure and a new stochastic beam search algo...
Abstract. Ant Colony Optimization (ACO) is a paradigm that employs a set of cooperating agents to solve functions or obtain good solutions for combinatorial optimization problems. ...
We propose an improved restart strategy for randomized backtrack search, and evaluate its performance by comparing to other heuristic and stochastic search techniques for solving r...
Beam-ACO algorithms are hybrid methods that combine the metaheuristic ant colony optimization with beam search. They heavily rely on accurate and computationally inexpensive boundi...
Combinatorial auctions (CAs) have emerged as an important model in economics and show promise as a useful tool for tackling resource allocation in AI. Unfortunately, winner determ...