Multicontextual dispatching rules for job shops with dynamic job arrival

The dynamic job shop problem is more challenging than the static job shop problem because dynamic job shops are disrupted by unforeseen events such as job arrivals and machine breakdowns. Each phase of a dynamic job shop problem presents a unique set of circumstances; multicontextual functions can describe the unique characteristics of a dynamic job shop at a specific time. The present work examines 11 basic dispatching rules and 33 composite rules made with multicontextual functions (MCFs) that describe machine idle time (MIT) and job waiting time (JWT). Simple procedures are presented that allow one or both of MIT and JWT to be combined with a single basic dispatching rule. This procedure produced 33 composite dispatching rules; the schedules from all 44 rules for a job shop with dynamic job arrival were compared with regard to make span and mean flow time. One composite rule, most work remaining with MCF2, produced schedules with the shortest make spans in 21 out of 27 cases; another composite rule, most remaining operations (MRO) with MCF3, produced schedules with the shortest mean flow times in 27 out of 27 cases. It was possible to combine JWT and MIT usefully only when the relevant dispatching rule did not depend on operation processing time; because MRO did not consider processing time, it benefitted from both JWT and MIT. Clients who demand short mean flow times might benefit from an implementation of MRO with MCF3.