scholarly journals A modified integer and categorical PSO algorithm for solving integrated process planning, dynamic scheduling and due date assignment problem

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Caner Erden ◽  
Halil Ibrahim Demir ◽  
Onur Canpolat
Keyword(s):  
Process Planning ◽  
Assignment Problem ◽  
Dynamic Scheduling ◽  
Pso Algorithm ◽  
Integrated Process ◽  
Due Date ◽  
Due Date Assignment

scholarly journals Solving Integrated Process Planning, Dynamic Scheduling, and Due Date Assignment Using Metaheuristic Algorithms

2019 ◽  
Vol 2019 ◽  
pp. 1-19 ◽  
Author(s):  
Caner Erden ◽  
Halil Ibrahim Demir ◽  
Abdullah Hulusi Kökçam
Keyword(s):  
Process Planning ◽  
Production Efficiency ◽  
Dynamic Scheduling ◽  
Metaheuristic Algorithms ◽  
Shop Floor ◽  
Integrated Process ◽  
Due Dates ◽  
Due Date ◽  
Planning And Scheduling ◽  
Due Date Assignment

Because the alternative process plans have significant contributions to the production efficiency of a manufacturing system, researchers have studied the integration of manufacturing functions, which can be divided into two groups, namely, integrated process planning and scheduling (IPPS) and scheduling with due date assignment (SWDDA). Although IPPS and SWDDA are well-known and solved problems in the literature, there are limited works on integration of process planning, scheduling, and due date assignment (IPPSDDA). In this study, due date assignment function was added to IPPS in a dynamic manufacturing environment. And the studied problem was introduced as dynamic integrated process planning, scheduling, and due date assignment (DIPPSDDA). The objective function of DIPPSDDA is to minimize earliness and tardiness (E/T) and determine due dates for each job. Furthermore, four different pure metaheuristic algorithms which are genetic algorithm (GA), tabu algorithm (TA), simulated annealing (SA), and their hybrid (combination) algorithms GA/SA and GA/TA have been developed to facilitate and optimize DIPPSDDA on the 8 different sized shop floors. The performance comparisons of the algorithms for each shop floor have been given to show the efficiency and effectiveness of the algorithms used. In conclusion, computational results show that the proposed combination algorithms are competitive, give better results than pure metaheuristics, and can effectively generate good solutions for DIPPSDDA problems.

scholarly journals Integrated process planning, WSPT scheduling and WSLK due-date assignment using genetic algorithms and evolutionary strategies

2017 ◽  
Vol 8 (1) ◽  
pp. 73-83
Author(s):  
Halil Ibrahim Demir ◽  
Onur Canpolat
Keyword(s):  
Genetic Algorithms ◽  
Process Planning ◽  
Random Search ◽  
Evolutionary Strategies ◽  
Integrated Process ◽  
Due Dates ◽  
Due Date ◽  
Planning And Scheduling ◽  
Due Date Assignment ◽  
Genetic Search

Process planning, scheduling and due-date assignment are three important manufacturing functions in our life. They all try to get local optima and there can be enormous loss in overall performance value if they are handled separately. That is why they should be handled concurrently. Although integrated process planning and scheduling with due date assignment problem is not addressed much in the literature, there are numerous works on integrated process planning and scheduling and many works on scheduling with due date assignment. Most of the works in the literature assign common due date for the jobs waiting and due dates are determined without taking into account of the weights of the customers. Here process planning function is integrated with weighted shortest processing times (WSPT) scheduling and weighted slack (WSLK) due date assignment. In this study unique due dates are given to each customer and important customers gets closer due dates. Integration of these three functions is tested for different levels of integration with genetic algorithms, evolutionary strategies, hybrid genetic algorithms, hybrid evolutionary strategies and random search techniques. Best combinations are found as full integration with genetic search and hybrid genetic search. Integration of these three functions provided substantial improvements in global performance.

scholarly journals Modified honey bees mating optimization algorithm for multi-objective uncertain integrated process planning and scheduling problem

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092523 ◽  
Author(s):  
Xiaoyu Wen ◽  
Xinyu Li ◽  
Liang Gao ◽  
Kanghong Wang ◽  
Hao Li
Keyword(s):  
Process Planning ◽  
Optimization Algorithm ◽  
Honey Bees ◽  
Processing Time ◽  
Intelligent Manufacturing ◽  
Scheduling Problem ◽  
Integrated Process ◽  
Due Date ◽  
Planning And Scheduling ◽  
Multi Objective

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.

PROCESS PLANNING AND SCHEDULING WITH PPW DUE-DATE ASSIGNMENT USING HYBRID SEARCH

2017 ◽  
Vol 2 (1) ◽  
pp. 20-38 ◽  
Author(s):  
Halil Ibrahim Demir ◽  
◽  
Tarık Cakar ◽  
Mumtaz Ipek ◽  
Burak Erkayman ◽  
...  
Keyword(s):  
Process Planning ◽  
Due Date ◽  
Hybrid Search ◽  
Planning And Scheduling ◽  
Due Date Assignment
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