A new admissible heuristic for the job shop scheduling problem with total flow time
Subject:
Heuristic search
Job shop scheduling
Total flow time
Publication date:
Editorial:
Association for the Advancement of Artificial Intelligence
Abstract:
In this paper, we face the Job Shop Scheduling problem with total flow time minimization with A∗ Nilsson’s algorithm. We propose a new heuristic based on problem relaxation to One Machine Sequencing problem with tardiness minimization. This heuristic is improved by means of the well-known generalized Emmons’ constraint propagation rules. Additionally, we use a pruning by dominance method to reduce the effective search space. We report results from an experimental study conducted to evaluate the performance of the proposed heuristic and to compare the A* approach with a classic local search procedure. The results show that the proposed heuristic is efficient as A* is able to reach optimal solutions for instances that are not always solved to optimality with the local search procedure; even running for a larger time
In this paper, we face the Job Shop Scheduling problem with total flow time minimization with A∗ Nilsson’s algorithm. We propose a new heuristic based on problem relaxation to One Machine Sequencing problem with tardiness minimization. This heuristic is improved by means of the well-known generalized Emmons’ constraint propagation rules. Additionally, we use a pruning by dominance method to reduce the effective search space. We report results from an experimental study conducted to evaluate the performance of the proposed heuristic and to compare the A* approach with a classic local search procedure. The results show that the proposed heuristic is efficient as A* is able to reach optimal solutions for instances that are not always solved to optimality with the local search procedure; even running for a larger time
Patrocinado por:
This work has been supported by the Spanish Ministry of Science and Education under research project MEC-FEDER TIN2007-67466-C02-01
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