Modeling And Optimization Research Of Flexible Job Shop Scheduling Under Time-of-use Price Policy

With the lack and the rising price of energy in domestic and overseas,energy is not only related to the economic benefits of enterprises, but also restricts the survival and development of energy-intensive enterprise.In production and operations management, by reducing energy consumption to reduce production costs become an impotant consideration of enterprise production scheduling.Time-of-use(TOU) pricing encourages enterprises to consume electricity in times of valley-load to reduce energy expense as well as relieve the tense situation of power supply.But adding the considerations of TOU,indirect energy and time cost into flexible job-shop scheduling problem(FJSP) making it more intricate.This paper introduced TOU,indirect energy and time cost to FJSP,and builded the Petri net model of this problem.It also proposed time selection strategies simulation algorithm of cost and genetic algorithm based on Petri net to find the most optimal scheduling scheme.The main work of this dissertation can be summarized as follows:(1)We formalized flexible job shop scheduling problem with time-of-use,indirect energy and time cost(TIT-FJSP),confirmed assumptions and constraints and to deduce the cost calculation.(2)We builded the Petri net model of TIT-FJSP. The model formalizes time,energy and concurrency constraints of TIT-FJSP. The execution assignments on the machine are abstracted to transitions,and the processing status of each task and each machine are abstracted as storages.We took direct energy, indirect energy and time cost as the combination elements,presented seven times selection strategies and cost simulation algorithm which supports non-continuous production scheduling to solve time selection of execution.(3)Based on the Petri net model and cost simulation algorithm above,we proposed an improved genetic algorithm to optimize machine assignments. Encoding transitons as chromosome and adopting double mutations, which are gene substance mutation and gene position mutation.This improved the convergence and search capability of genitic algorithm,and finally seeked the non-dominated solution of TIL-FJSP.At last, the paper carried on simulation and cases tests of the TIL-FJSP model and algorithm.First, we generated test cases to test time selection strategies,considerations andthe efficiency of algorithm,it verified the effectiveness of the algorithm Finally, the scheduling solution and optimization method were tested in a specific tire banbury level.The resuts showed that, compared with only considering time costs, taking time cost and TOU into acount can save 36.7% of the production cost.Adding the considerations of time cost,TOU and indirect energy still can further tap more than 3% potential of saving production expense.