Parallel Machine Scheduling Problem With Working-mode Assignment And Deteriorating Effect

The traditional researches on production scheduling problem usually focus on the deterministic environment,and datas related to the problem are known in advance.However,in actual production scheduling,there is a phenomenon that the processing time of a job changes with its start time.It is called "production scheduling problem with deteriorating effect".On the other hand,the relationship between production indicators and natural environment is constantly changing.The rational utilization and distribution of resources and energy is of vital importance for the survival and sustainable development of enterprises.It is urgent for enterprises to change the traditional production management mode,reasonably assign scheduling resources through modern scheduling technology and collaboratively optimize energy consumption,delay,cost and other production indicators.Based on the production scenario with deteriorating effect,the optimization of energy consumption and delay cost will greatly expand this kind of scheduling research,which has important academic research and engineering application value.In this paper,the scheduling problem of parallel machines with deteriorating effect is studied,and the working mode assignment scenario is introduced.The aim of this paper is to design efficient scheduling algorithms and discuss the solution method of green scheduling problem considering the delay cost and energy consumption cost.The main contributions of this dissertation are listed below:(1)This paper deals with the scheduling problem of parallel machines with working mode assignment and deteriorating effect.In order to minimize the total energy consumption and total delay cost,a mixed integer programming model is constructed and the probability assignment strategy is also designed to assign the working mode.Besides,an improved particle swarm optimization algorithm is proposed based on the characteristics of the problem.It designs the current state update,cognitive mode update and social mode update to replace the update method of standard particle swarm optimization algorithm.Meanwhile,the crossover variation operation of genetic algorithm is also adopted to it.The experimental results show that compared with the existing heuristic algorithm,the proposed algorithm can effectively improve the accuracy of problem solving and optimization efficiency.(2)There are some limitations in the accuracy of the solution obtained by heuristic algorithm.In order to further improve the accuracy of the solution in a reasonable time,the Logical-Based Benders Decomposition algorithm is designed.The algorithm decomposes the original problem model into a master problem and several parallel subproblems.The master problem and subproblems iterate continuously with benders cut to converge to the optimal solution.In addition,two improvement measures are designed to increase the convergence speed of the master problem and subproblems.The performance of the proposed algorithm is verified by a number of test cases with different scales.(3)The original problem is extended to not only consider the scheduling costs of processing jobs but also the benefits of them.The mixed integer programming model is constructed.At the same time,a hybrid Benders decomposition algorithm is designed.An improved water wave algorithm is used to solve the subproblems based on the framework of logical based benders decomposition.It improves the speed of subproblem solving using MIP model.The example tests show that the hybrid Benders decomposition algorithm can further improve the solving accuracy.The research of production scheduling with deterioration effect fits the actual production situation,and the reasonable assignment of working mode will reduce energy consumption and delay.Based on the requirements of actual production scheduling for economic development and sustainable development,the production scenario is set with deteriorating effect and considering the assignment of working mode to co-optimize the energy consumption and delay cost of parallel machine scheduling problem.It enriches the research of green modern scheduling problem and has important practical significance and application value.