CAJ | 학술논문

针对产品处理时间不确定条件下中间存储时间有限多产品间歇生产过程调度问题，采用三角模糊数描述处理时间的不确定性，通过一种模糊排序的方法建立了以最小化模糊最大完工时间的值以及不确定度作为调度目标的数学模型，提出一种基于改进粒子群和分布估计的混合算法(IPSO-EDA)。IPSO-EDA算法在粒子群更新公式中引入基于所有粒子自身最优位置的优质个体分布信息，提高了算法的全局搜索能力，同时采用 NEH 初始化获得理想的初始解，采用 NEH 局部搜索提高算法的局部搜索能力。通过正交实验设计对算法的参数进行调节，仿真结果表明了所提出算法的有效性和优越性。
침대산품처리시간불학정조건하중간존저시간유한다산품간헐생산과정조도문제，채용삼각모호수묘술처리시간적불학정성，통과일충모호배서적방법건립료이최소화모호최대완공시간적치이급불학정도작위조도목표적수학모형，제출일충기우개진입자군화분포고계적혼합산법(IPSO-EDA)。IPSO-EDA산법재입자군경신공식중인입기우소유입자자신최우위치적우질개체분포신식，제고료산법적전국수색능력，동시채용 NEH 초시화획득이상적초시해，채용 NEH 국부수색제고산법적국부수색능력。통과정교실험설계대산법적삼수진행조절，방진결과표명료소제출산법적유효성화우월성。
Time-constrained intermediate storage multiproduct batch process scheduling with uncertain processing time is concerned in this paper. The triangular fuzzy number is applied to describe the imprecise processing time of products. An approach for ranking fuzzy numbers is used to estimate the value and uncertainty of the makespan which are employed to establish the mathematical model. An improved particle swarm optimization with estimation of distribution algorithm (IPSO-EDA) is proposed. The IPSO-EDA incorporates the global statistical information collected from personal best solutions of all particles into the particle swarm optimization (PSO), and therefore each particle has comprehensive search ability. Meanwhile, the NEH-based initialization and local search are introduced to construct good initial solutions and enhance the local exploitation, respectively. In addition, the influence of parameter settings of the IPSO-EDA is investigated based on the method of factorial design. The simulation results indicate the superiority of IPSO-EDA in terms of effectiveness and efficiency.