Authors:
María R. Sierra
1
and
Ramiro Varela
2
Affiliations:
1
University of Cantabria, Facultad de Ciencias, Spain
;
2
University of Oviedo, Spain
Keyword(s):
Heuristic Search, Best First Search, Pruning by Dominance, Job Shop Scheduling.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Enterprise Software Technologies
;
Intelligent Problem Solving
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Software Engineering
;
Symbolic Systems
Abstract:
Best-first graph search is a classic problem solving paradigm capable of obtaining exact solutions to optimization problems. As it usually requires a large amount of memory to store the effective search space, in practice it is only suitable for small instances. In this paper, we propose a pruning method, based on dominance relations among states, for reducing the search space. We apply this method to an A∗ algorithm that explores the space of active schedules for the Job Shop Scheduling Problem with makespan minimization. The A∗ algorithm is guided by a consistent heuristic and it is combined with a greedy algorithm to obtain upper bounds during the search process. We conducted an experimental study over a conventional benchmark. The results show that the proposed method is able to reduce both the space and the time in searching for optimal schedules so as it is able to solve instances with 20 jobs and 5 machines or 9 jobs and 9 machines. Also, the A∗ is exploited with heuristic wei
ghting to obtain sub-optimal solutions for larger instances.
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