关键词: 作业车间, 分批调度, 可变分批, 子批混排, 进化算法

Abstract:  For solving the lot streaming job shop scheduling， a strategy was presented integrating variable sublots splitting and sublots intermingling， and a multi-objective optimization model of lot streaming scheduling was established to minimize the energy consumption and makespan. An improved multi-objective hybrid evolutionary algorithm was presented. In order to balance the global and local searching ability of the algorithm， the population updating mechanism of the Jaya algorithm was incorporated into the decomposition based multi-objective evolutionary algorithm. Considering the scheduling characteristics of variable lot splitting and sublots intermingling， a local searching strategy was designed integrating lot splitting/merging with critical path. The performance of the proposed algorithm and the state-of-the-art algorithms were compared under a set of instances of different scales. Experimental results show that the proposed algorithm has good performance on the convergence and distribution of Pareto solution sets. Moreover， the proposed variable lot splitting and sublots intermingling strategy may effectively reduce the energy consumption and makespan. 

Key words:  , job shop, lot streaming scheduling, variable lot splitting, sublots intermingling, evolutionary algorithm