On Job-shop Scheduling By Improved Quantum Genetic Algorithm

Production scheduling is a core of the entire production system for advanced management techniques and technology planning, optimization, automation, the development of computer technology.Study research and application of effective method of scheduling and optimization technology of advanced manufacturing and raise the efficiency of production is very important.GA is one of the most widely evolutionary computation methods in scheduling optimization.For production scheduling for a typical job-shop scheduling problem (Job-Shop Scheduling Problem), the author deeply study the standard genetic algorithm and quantum genetic algorithm. This paper presents an improved quantum genetic algorithm. The algorithm for quantum evolution of the genetic algorithm early, medium and late has the shortcomings and limitations, the introduction of the elite database, and interfere database and the rotation angle of adaptive changes to overcome quantum genetic algorithm's entire evolutionary shortcomings. The elite in the early evolutionary algorithm's effect is obviously, the use of elite outstanding individual to replace evolution of the worst individual, which would greatly enhance the early evolutionary algorithm's optimization speed; The direction of cross-mechanism algorithm determines the efficiency of cross-operate to guarantee the genetic algorithm optimization process, and can improve optimization process,and it plays an important role, as long as the genetic algorithm with Quantum revolving door for quantum cross, as quantum rotation angle on the choice is particularly important. Adaptive conditioning rotation angle will prevent the quantum genetic algorithm identified by the beginning from finding solution, for adaption of rotating angle adjustment, so that the convergence rate algorithm greatly enhanced. When the algorithm reaches a certain stage in the evolution of population stagnation or slow development stage, improved genetic algorithm introduced quantum interference library, interference with the use of artificial evolution of the population interference from the evolutionary algorithm stagnation as soon as possible to begin a new search.Through the standard genetic algorithm, quantum genetic algorithm and Improvement Quantum Genetic Algorithm's comparison, the author use function testing examples of job-shop scheduling, effectively proved the superiority of the improved algorithm in solving job-shop scheduling problems.