Minimizing the expected maximum lateness for a job shop subject to stochastic machine breakdowns

• Published in: Annals of operations research Vol. 338; no. 1; pp. 801 - 833
• Main Authors: Zambrano-Rey, Gabriel Mauricio, González-Neira, Eliana María, Forero-Ortiz, Gabriel Fernando, Ocampo-Monsalve, María José, Rivera-Torres, Andrea
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.07.2024; Springer; Springer Nature B.V
• Subjects: Algorithms; Business and Management; Coefficient of variation; Combinatorics; Computer simulation; Dispatching rules; Integer programming; Job shop scheduling; Job shops; Lateness; Linear programming; Methods; Mixed integer; Monte Carlo method; Monte Carlo simulation; Operations Research/Decision Theory; Original Research; Performance evaluation; Scheduling (Management); Tabu search; Theory of Computation; Colombia; Machine breakdowns; Stochastic job shop scheduling; Tabu search; Simheuristics; Maximum lateness

This paper addresses a stochastic job shop scheduling problem with sequence-dependent setup times, aiming to minimize the expected maximum lateness. The stochastic nature is modeled by considering uncertain times between failures (TBF) and uncertain times to repair (TTR). To tackle this problem, a s...