scholarly journals A priority-based heuristic algorithm (PBHA) for optimizing integrated process planning and scheduling problem

2015 ◽  
Vol 2 (1) ◽  
pp. 1070494 ◽  
Author(s):  
Muhammad Farhan Ausaf ◽  
Liang Gao ◽  
Xinyu Li ◽  
Ghiath Al Aqel
2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Shuai Zhang ◽  
Yangbing Xu ◽  
Zhinan Yu ◽  
Wenyu Zhang ◽  
Dejian Yu

Distributed integration of process planning and scheduling (DIPPS) extends traditional integrated process planning and scheduling (IPPS) by considering the distributed features of manufacturing. In this study, we first establish a mathematical model which contains all constraints for the DIPPS problem. Then, the imperialist competitive algorithm (ICA) is extended to effectively solve the DIPPS problem by improving country structure, assimilation strategy, and adding resistance procedure. Next, the genetic algorithm (GA) is adapted to maintain the robustness of the plan and schedule after machine breakdown. Finally, we perform a two-stage experiment to prove the effectiveness and efficiency of extended ICA and GA in solving DIPPS problem with machine breakdown.


2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092523 ◽  
Author(s):  
Xiaoyu Wen ◽  
Xinyu Li ◽  
Liang Gao ◽  
Kanghong Wang ◽  
Hao Li

The new technology of intelligent manufacturing makes the data of process planning and shop scheduling easier to interconnect, and the integration optimization of different manufacturing processes is an important technology to ensure the implementation of intelligent manufacturing. Integrated process planning and scheduling is a significant research focus in recent years, which could improve the performance of manufacturing system. At present, the research on integrated process planning and scheduling is insufficient to consider the multi-objective and uncertain characteristics widely existing in real manufacturing environment. Therefore, multi-objective integrated process planning and scheduling problem with uncertain processing time and due date is addressed in this article. The mathematical model of multi-objective uncertain integrated process planning and scheduling problem with uncertain processing time and fuzzy due date is established based on fuzzy set, in which the calculation method of uncertainty measurement objective is designed. An effective modified honey bees mating optimization algorithm has been designed to solve the proposed model. Queens set is constructed to maintain the non-dominated solutions found in the optimization process. The calculation method of mating probability between drone and queen bee based on Euclidean distance is designed. Fuzzy operators were utilized to evaluate fitness, judge the non-dominated relationship, and decode the scheduling solution. Different instances were designed and carried out to test the performance of the proposed method. The results show that the proposed method is very effective for solving multi-objective uncertain integrated process planning and scheduling.


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