Abstract

The open-shop scheduling problem is concerned with the allocation of tasks to resources, especially when resources are scarce. The problem has many practical applications in the production, manufacturing, testing, and telecommunication domains. In this paper, we study the non-preemptive open-shop scheduling problem with more than two machines using two metaheuristic algorithms: cuckoo search and ant colony optimization. The proposed algorithms are implemented using Python, and tested on the Taillard benchmarks. Favorable results comparisons are reported.

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