Research On Dynamic Scheduling Optimization In Flexible Job Shop Considering Energy Consumption

Green development is one of the basic policy of Made in China 2025, which is the first ten-year plan of our country to implement the strategy of manufacturing power. Green manufacturing by considering energy consumption has become a new trendency. In addition, with the advent of the Industrial 4.0 era, customer demand for products is increasingly diversified and personalized. And the actual production scheduling interferences may often occur, such as machine fault, new workpiece reach. So dynamic flexible job-shop scheduling optimization problem(DFJSP) by considering energy consumption is studied in this paper.Frist of all, the categorization of shop interferences was discussed. Machine fault, new workpiece reach(including emergency insert), workpiece cancellation, processing time change and so on four kinds of typical interference events were selected. Based on the reasearch of dynamic scheduling strategy and rolling window technology, hybrid rescheduling strategy based on events and cycle, completely rescheduling method and rolling window optimization technique were adopted. According to the actual situation, the multi-objective optimization mathematical model of DFJSP by considering simultaneously scheduling efficiency, stability and energy consumption was established. The scheduling efficiency, stability performance and energy consumption are respectively characterized with minimum makespan, process start time deviation before and after rescheduling and sum of machining energy, idling energy and logistics energy.Secondly, a hybrid algorithm of improved GA and pareto optimization was designed, which has a new population initialization. In order to make the hybrid optimization algorithm be suitable for dynamic scheduling problem, based on rolling window technology, dynamic scheduling updating and merging technology were designed, which includes original data update technology and scheme merging technology. The simulation results verify that the new population initialization method can effectively improve the optimization algorithm performance and the effectiveness and superiority of the hybr id optimization method. And dynamic scheduling updating and merging technology can effectively deal with DFJSP under the above four kinds of plant interferences.Then, the systematic optimization study of DFJSP from a single, double and multi-objective and so on three aspects through a simple case with the hybrid optimization algorithm. The simulation results show that the multi-objective has more advantages. Because of its scheduling optimization results is a set of pareto optimal solutions, but also comparing the influence of transport factors on scheduling optimization results, so it can make the production scheduling decision makers have larger and more scientific choice space.Finally, according to China's machinery industry standards, the flexible job shop scheduling case was designed. Under the dynamic circumstances of heavier task scheduling and more complex of interference events, the above DFJSP model and the hybird optimization algorithm are analyed in the results and emulational verified.