Resource allocation model and deadlock-free optimization scheduling for underground locomotive transportation.

A deadlock-free scheduling scheme and optimization for underground locomotive transportation system are presented. Firstly, three resource allocation Petri net models under different dispatching policies are modeled, their corresponding maximal makings boundary setting algorithms are designed, and the deadlock-free property of dispatching under maximal marking boundary setting is proved. Then, a genetic algorithm is proposed to minimize the time cost and energy cost, in which the transitions sequence is encoded as a chromosome, the feasibility of chromosomes are tested and amended by judging the transition firing condition, so that each chromosome can be decoded into a feasible schedule to satisfy all resource allocation constraints. Finally, an experimental example is simulated. The designed maximal marking boundary setting algorithm of deadlock-free schedule and genetic algorithm provide reliable theoretical foundation for underground locomotive transportation dispatching. [ABSTRACT FROM AUTHOR]