Abstract
This paper presents a new algorithm that obtains an approximation of the Critical Path in schedules generated using the disjunctive graph model that represents the Job Shop Scheduling Problem (JSSP). This algorithm selects a set of operations in the JSSP, where on the average ninety nine percent of the total operations that belong to the set are part of the critical path. A comparison is made of cost and performance between the proposed algorithm, CPA (Critical Path Approximation), and the classic algorithm, CPM (Critical Path Method). With the obtained results, it is demonstrated that the proposed algorithm is very efficient and effective at generating neighborhoods in the simulated annealing algorithm for the JSSP.
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Cruz-Chávez, M.A., Frausto-Solís, J. (2006). A New Algorithm That Obtains an Approximation of the Critical Path in the Job Shop Scheduling Problem. In: Gelbukh, A., Reyes-Garcia, C.A. (eds) MICAI 2006: Advances in Artificial Intelligence. MICAI 2006. Lecture Notes in Computer Science(), vol 4293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11925231_42
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DOI: https://doi.org/10.1007/11925231_42
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