A global-local neighborhood search algorithm and tabu search for flexible job shop scheduling problem

• DOI: 10.7717/peerj-cs.574
• Publication Date: 2021-05-27T07:39:36Z
• Authors: Nayeli Jazmin Esc...; Juan Carlos Seck-...; Joselito Medina-M...; Norberto Hernande...; Irving Barragan-Vite; Jose Ramon Corona...
• Keywords: Guided Local Search; Job shop; Benchmark (surveying); Hill climbing

The Flexible Job Shop Scheduling Problem (FJSP) is a combinatorial problem that continues to be studied extensively due its practical implications in manufacturing systems and emerging new variants, order model optimize more complex situations reflect the current needs of industry better. This work presents metaheuristic algorithm called global-local neighborhood search (GLNSA), which concepts cellular automaton are used, so set leading solutions smart-cells generates shares information helps instances FJSP. GLNSA accompanied by tabu implements simplified version Nopt1 defined Mastrolilli & Gambardella (2000) complement optimization task. experiments carried out show satisfactory performance proposed algorithm, compared with other results published recent algorithms, using four benchmark sets 101 test problems.