Multi-objective approach to optimize production and maintenance scheduling in flow shop environment under non-renewable resources constraints

Traditional scheduling problems deal with machines as the only type of resource needed to conduct production tasks. In reality, other types of resources such as raw materials, tools, chemical ingredients …etc. often have a great impact on production in many real-world applications. In addition, maintenance services are also implicated in the manufacturing process; their goal is to sustain the production system and keep the machines in healthy operating conditions. This paper deals with a bi-objective permutation flowshop scheduling, and maintenance planning problem subject to limited non-renewable resources supplied from outside the system with deterministic quantities at predetermined moments. The well-known Second version of the Non Dominated Sorting Genetic Algorithm (NSGA-II) is adopted to deal with the problem and obtain approximate non-dominated sets in reasonable time.