Flexible job-shop scheduling problem with job precedence constraints and interval grey processing time

In the practical production scheduling of complex products, the processing time always fails to be accurately estimated as a deterministic value due to the fluctuating manufacturing environment caused by unsteady operating conditions of machines and diverse proficiency levels of workers. Besides, scheduling jobs become restricted by precedence constraints on account of the hierarchical dependencies between manufactured parts defined by Bills-Of-Materials of final products. Hence, this study concentrates on the flexible job shop scheduling problem with job precedence constraints and interval grey processing time (G-FJSP-JPC) under the objective of minimizing the interval grey makespan. The uncertain processing time as well as other time data are represented as interval grey numbers with lower and upper boundaries. Specific operators for dealing with interval grey time numbers are devised to acquire precise grey schedules. A two-vector encoding scheme with job precedence repair mechanism is employed and a heuristic active grey decoding scheme is proposed in which the machine assignment is dynamically determined and the uncertain grey schedule is constructed. A novel multi-micro-swarm leadership hierarchy-based optimization algorithm (M2SLHO) is proposed to tackle G-FJSP-JPC. This algorithm divides search agents into multiple independent micro-swarms in which each one conducts a leadership hierarchy-based search and communicates with others by specific strategies. Extensive computational experiments validate that M2SLHO provides highly promising results for the addressed problem.