CAJ | 학술논문

为提高车间调度算法的寻优性能，提出了一种基于维信息共享的粒子群算法的车间调度问题解决方案。该算法对粒子群的认知过程和更新过程进行了研究，通过维信息共享和动态认知概念的引入，实现了优化问题维信息的沟通和交流，通过增加扰动因子克服算法的过早收敛，提高了对优化问题的适应能力。通过对3个连续函数优化问题的测试，得到了最佳的平均值和标准差，并对14个JSP标准测试案例进行仿真。结果表明无论是在求解质量还是收敛速度方面都优于其他几种算法，说明该算法能够有效地、高质量地解决作业车间调度问题。
위제고차간조도산법적심우성능，제출료일충기우유신식공향적입자군산법적차간조도문제해결방안。해산법대입자군적인지과정화경신과정진행료연구，통과유신식공향화동태인지개념적인입，실현료우화문제유신식적구통화교류，통과증가우동인자극복산법적과조수렴，제고료대우화문제적괄응능력。통과대3개련속함수우화문제적측시，득도료최가적평균치화표준차，병대14개JSP표준측시안례진행방진。결과표명무론시재구해질량환시수렴속도방면도우우기타궤충산법，설명해산법능구유효지、고질량지해결작업차간조도문제。
In order to improve the performance of shop scheduling algorithm , a dimensional information sharing-based particle swarm optimization ( PSO) algorithm for workshop scheduling problem is proposed . The cognitive process and update process of particle swarm are studied .By introducing the concept of di-mensional information sharing and dynamically cognizing , dimensional information of optimization problem can be communicated and exchanged .The power of adapting to optimization problem of PSO is increased through adding disturbance factor to overcome premature convergence of the algorithm .Finally, the best mean value and the standard deviation are obtained through test of three continuous function optimization problems.The simulation results of fourteen standard test cases for JSP show that the algorithm is better than several other algorithms both in terms of solution quality and convergence speed .The results illustrate that the algorithm can solve the workshop scheduling problem with high efficiency and quality .