Study And Application On Jobshop Scheduling Problem Based On Genetic Algorithm

With the increasing keen market competition, each enterprise looks for better solutions to production and operation management aiming at improve the core competitive advantage.The key to the management of production and operation management is to achieve the optimal solutions.Therefore, the study of Job shop scheduling is of great significance.The paper presents the definition of Job shop scheduling problem and analyzes the characteristics and discusses the computational complexity. Meanwhile, it reviews the main procedure and research ways of Job shop scheduling problem.Based on the previous research by scientists in JSP field,the paper also introduces the object to Job shop scheduling problem of its kind and research status quo. It deals with the mathmatical models and relevant algorithms respectively: heuristic and genetic algorithms. First, it focuses on the study of relevant algorithms such as evolutional algorithms and researching. Secondly, the research of adjusted algorithm based on standard genetic algorithm is studied.The paper proposes a hybrid algorithm based on standard genetic algorithm with heuristic rules (shorest processing time and most work remaining) and discusses the effect on optimal results by making use of the various coding, crossover operators and mutation operators. Then we make an introduction to scheduling optimal strategies and procedures.The algorithm diminishes the searching space by using heuristic rules remarkablely. It is easier and quicker to find the optimal results than the standard one.Finally, the paper offers the design and realization of JSP algorithm and discusses its complexity and convergence.