Genetic algorithms for single machine scheduling with time-dependent deterioration and rate-modifying activities

In this paper, the integration of two emerging classes of scheduling problems, the class of scheduling problems with time-dependent deterioration and the class of scheduling problems with rate-modifying activities, are addressed. The scheduling problems have been studied independently. However, the integration of these classes is motivated by human operators of tasks who have fatigue while carrying out the operation of a series of tasks. This situation is also applicable to machines that experience performance degradation over time due to mal-position or mal-alignment of jobs, abrasion of tools, and scraps of operations, etc. It requires maintenance in order to sustain acceptable production rates. We consider the single machine scheduling problem with time-dependent deterioration and multiple RMAs. A mathematical model for an optimal solution to minimize the makespan is derived and genetic algorithms are proposed. The performance of the genetic algorithms is evaluated using randomly generated examples.

► We consider single machine scheduling with time-dependent deterioration and RMAs. ► We derive a mathematical model to minimize the makespan for the scheduling problem. ► We propose genetic algorithms (GAs) with three different chromosome types. ► We evaluate the performances of the GAs using several randomly generated examples.