Research On NSGA-Ⅱ Improved Algorithm And Johnson＿IG Algorithm For Solving Flow Shop Scheduling Under TOU

In order to better utilize energy for manufacturing enterprises and achieve the goal of peak shaving and valley filling in electricity use,China has formulated a series of targeted measures,among which the most widely used is time-of-use electricity pricing.The implementation of time-of-use electricity prices affects the production arrangements of manufacturing enterprises on the one hand,and increases their manufacturing costs on the other hand.In this context,studying the most common flow shop scheduling in manufacturing under TOU to improve production efficiency while reducing power costs is a realistic issue that management decision-makers urgently need to address.Based on the flow shop scheduling problem under TOU,this paper studies an efficient solution algorithm for synchronous optimization of production efficiency and power cost.Firstly,according to the characteristics of the problem,a dual objective mathematical optimization model for flow shop scheduling under TOU is constructed.Based on the traditional completion time minimization model,a universal time window calculation formula is proposed.Within the allowable range of the time window,a joint optimization mathematical model with the goal of minimizing the total power cost is constructed.Secondly,an accelerated right shift operation with a branching strategy is designed to improve the NSGA-II algorithm for the dual objective mathematical optimization model,thereby achieving group iterative optimization.Then,aiming at the mathematical model of joint optimization,a new Johnson＿IG algorithm is designed to achieve individual iterative optimization,which conforms to the characteristics of this study.Finally,small and large-scale examples of Taillard are randomly selected for simulation experiments to analyze the effectiveness and feasibility of the algorithm.The experimental results show that the right shift operation after the introduction of the acceleration strategy reduces the computational time by 67%,and the improved NSGA-II algorithm has better quality Pareto solution sets compared to the previous one,and provides 1.72 times as many non dominated solution sets as the previous one.Further analyzing the experimental comparison results,it can be concluded that when solving small-scale flow shop scheduling problems under TOU,the quality of the solution obtained by using the Johnson＿IG algorithm is superior to the improved NSGA-II algorithm.When solving large-scale flow shop scheduling problems under TOU,the quality of the solution obtained by using the improved NSGA-II algorithm is superior to the Johnson＿IG algorithm.