Production capacity planning and scheduling in a no-wait environment with controllable processing times: An integrated modeling approach

This paper develops an integrated model between a production capacity planning and an operational scheduling decision making process in which a no-wait job shop (NWJS) scheduling problem is considered incorporating with controllable processing times. The duration of any operations are assumed to be controllable variables based on the amount of capacity allocated to them, whereas in classical NWJS it is assumed that the machine capacity and hence processing times are fixed and known in advance. The suggested problem which is entitled no-wait job shop crashing (NWJSC) problem is decomposed into the crashing, sequencing and timetabling subproblems. To tackle the addressed NWJSC problem, an improved hybrid timetabling procedure is suggested by employing the concept of both non-delay and enhanced algorithms which provides better solution than each one separately. Furthermore, an effective two-phase genetic algorithm approach is devised integrating with hybrid timetabling to deal with the crashing and sequencing components. The results obtained from experimental evaluations support the outstanding performance of the proposed approach.

► In this study, we model integration between a production capacity planning and an operational scheduling problem. ► It was considered that duration of any operations is controllable variables based on the amount of capacity allocated to them. ► We suggested that the suggested problem is decomposed into the crashing, sequencing and timetabling subproblems. ► A new hybrid timetabling method is devised and integrated with a two-phase genetic algorithm approach to handle the proposed model. ► We find that the suggested approach is a reliable and effective technique for solving the integration model through a computational study.