Modern heuristic techniques for combinatorial problems
Modern heuristic techniques for combinatorial problems
A tutorial survey of job-shop scheduling problems using genetic algorithms—I: representation
Computers and Industrial Engineering
A fast taboo search algorithm for the job shop problem
Management Science
Guided Local Search with Shifting Bottleneck for Job Shop Scheduling
Management Science
Scheduling Computer and Manufacturing Processes
Scheduling Computer and Manufacturing Processes
Introduction to Algorithms
How to Solve It: Modern Heuristics
How to Solve It: Modern Heuristics
Computers and Operations Research - Anniversary focused issue of computers & operations research on tabu search
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The scheduling of manufacturing processes aims to find sequences of jobs on given machines optimal by a selected criterion, e.g. minimal completion time of all operations. With respect to NP-hardness of these problems and the necessity to solve them by heuristic methods, the problem representation and the effectiveness of their procedures is substantial for computations to be completed in a reasonable amount of time. In this paper, we deal with job shop scheduling problem (JSSP) in a disjunctive graph-based representation. Turning all undirected edges into directed ones, the problem is transformed to a problem solvable by the Critical Path Method (CPM). We propose an original implementation of the CPM that makes it possible to decrease its time complexity and thus also the running time of all JSSP iterations.