Introduction to operations research, 4th ed.
Introduction to operations research, 4th ed.
Job shop scheduling by simulated annealing
Operations Research
Genetic Algorithms in Engineering Systems
Genetic Algorithms in Engineering Systems
A Parallel Implementation of a Job Shop Scheduling Heuristic
PARA '00 Proceedings of the 5th International Workshop on Applied Parallel Computing, New Paradigms for HPC in Industry and Academia
An experimental analysis of local minima to improve neighbourhood search
Computers and Operations Research
Experimental Analysis of a Neighborhood Generation Mechanism Applied to Scheduling Problem
CERMA '06 Proceedings of the Electronics, Robotics and Automotive Mechanics Conference - Volume 02
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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.