Research on production planning and scheduling based on improved collaborative optimization

2019 ◽  
Vol 27 (2) ◽  
pp. 99-111 ◽  
Author(s):  
Song Zheng ◽  
Jiaxin Gao ◽  
Jian Xu
Keyword(s):  
Production Planning ◽  
Production Scheduling ◽  
Production Efficiency ◽  
Collaborative Optimization ◽  
Production Plan ◽  
The Novel ◽  
Integration Algorithm ◽  
Planning And Scheduling ◽  
Integrated Optimization ◽  
Production Planning And Scheduling

The production planning is aimed at the formulation and distribution of the overall production plan, while the production scheduling focuses on the implementation of the specific production plan. It is very important to coordinate each other in order to promote the production efficiency of enterprises, but the integrated optimization of production planning and scheduling has great challenges. This article proposes the novel integrated optimization method of planning and scheduling based on improved collaborative optimization. An integrated model of planning and scheduling with collaborative optimization structure is established, and the detailed solution strategy of the novel integrated optimization algorithm is presented. At last, the simulation results show that the proposed integration algorithm of planning and scheduling is competitive in global optimization and practicality.

Integrated optimization of production planning and scheduling in uncertain re-entrance environment for fixed-position assembly workshops

2022 ◽  
pp. 1-18
Author(s):  
Nan-Yun Jiang ◽  
Hong-Sen Yan
Keyword(s):  
Genetic Algorithm ◽  
Production Planning ◽  
Programming Model ◽  
Expected Value ◽  
Fixed Position ◽  
Planning And Scheduling ◽  
Integrated Optimization ◽  
Production Planning And Scheduling ◽  
Level Model ◽  
Upper Level

For the fixed-position assembly workshop, the integrated optimization problem of production planning and scheduling in the uncertain re-entrance environment is studied. Based on the situation of aircraft assembly workshops, the characteristics of fixed-position assembly workshop with uncertain re-entrance are abstracted. As the re-entrance repetition obeys some type of probability distribution, the expected value is used to describe the repetition, and a bi-level stochastic expected value programming model of integrated production planning and scheduling is constructed. Recursive expressions for start time and completion time of assembly classes and teams are confirmed. And the relation between the decision variable in the lower-level model of scheduling and the overtime and earliness of assembly classes and teams in the upper-level model of production planning is identified. Addressing the characteristics of bi-level programming model, an alternate iteration method based on Improved Genetic Algorithm (AI-IGA) is proposed to solve the models. Elite Genetic Algorithm (EGA) is introduced for the upper-level model of production planning, and Genetic Simulated Annealing Algorithm based on Stochastic Simulation Technique (SS-GSAA) is developed for the lower-level model of scheduling. Results from our experiments demonstrate that the proposed method is feasible for production planning and optimization of the fixed-position assembly workshop with uncertain re-entrance. And algorithm comparison verifies the effectiveness of the proposed algorithm.

An agent-based architecture for production scheduling in dynamic job-shop manufacturing system

2018 ◽  
Vol 66 (6) ◽  
pp. 492-502 ◽  
Author(s):  
Om Ji Shukla ◽  
Gunjan Soni ◽  
Rajesh Kumar ◽  
Sujil A
Keyword(s):  
Production Planning ◽  
Production Scheduling ◽  
Manufacturing System ◽  
Job Shop ◽  
Shop Floor ◽  
Efficient Production ◽  
Planning And Scheduling ◽  
Agent Based ◽  
Production Planning And Scheduling ◽  
Key Issues

Abstract In a highly competitive environment, effective production is one of the key issues which can be addressed by efficient production planning and scheduling in the manufacturing system. This paper develops an agent-based architecture which enables integration of production planning and scheduling. In addition, this architecture will facilitate real time production scheduling as well as provide a multi-agent system (MAS) platform on which multiple agents will interact to each other. A case study of job-shop manufacturing system (JMS) has been considered in this paper for implementing the concept of MAS. The modeling of JMS has been created in SimEvents which integrates an agent-based architecture developed by Stateflow to transform into dynamic JMS. Finally, the agent-based architecture is evaluated using utilization of each machine in the shop floor with respect to time.

PRODUCTION MANAGEMENT — SIMPLE OR COMPLEX

2004 ◽  
Vol 01 (04) ◽  
pp. 359-371 ◽  
Author(s):  
GIDEON HALEVI
Keyword(s):  
Production Planning ◽  
Production Scheduling ◽  
Production Management ◽  
Planning Method ◽  
Complex Task ◽  
Simple Task ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling ◽  
Planning Methods ◽  
Delivery Dates

Theoretical production planning and scheduling is actually very simple task: The plant gets orders which defines the product, the quantity and delivery dates. The resources of the plants are known, the product bill of material is known and the task of production scheduling is to make sure that the orders will be ready on time, that's all. It seems strange that in order to meet this simple task, over 100 complex production planning methods were proposed. Some of the outstanding ones are: PICS; MRP; ERP; GT; TOC; FMS; IMS; CIM; CE; JIT; Kanaban; TQM; Agent…, AGILE etc. Yet the search for "THE" method is carried on. In this paper an attempt to analyze why production planning is regarded as a complex task, and why the search for "THE" production planning method is still an open topic for researchers. Furthermore, to demonstrate how introduction of flexibility will restore the simplicity of production planning.

A Production Planning and Scheduling Architecture for Networked-Manufacturing System Based on Available-to-Promise

2011 ◽  
Vol 268-270 ◽  
pp. 292-296 ◽  
Author(s):  
Wen Hao Wang ◽  
Qiong Zhu ◽  
Jie Zhang
Keyword(s):  
Production Planning ◽  
Production Scheduling ◽  
Manufacturing System ◽  
Resource Planning ◽  
Networked Manufacturing ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling ◽  
Order Management ◽  
Production Activity ◽  
Decision Making System

In the practical application of push-pull based production planning and scheduling architecture, the manufacturing system was found lacking of collaborative mechanism, especially for a networked-manufacturing environment, which requires each individual manufacturer interact and cooperate with each other for a collaborative manufacturing. This paper presents a production planning and scheduling architecture for networked-manufacturing system based on available-to-promise, which can effectively merge forecast-driven production activity with order-driven production activity, thus ensures the steady and prompt supply of material, and also cooperation and mutual benefit of individual manufacturer. This architecture consists of 1) an ATP-based order management and decision-making system, 2) a push-pull based multi-plant master production schedule collaboration model, 3) a pre-reactive collaborative replenishment model, 4) a production scheduling model of unrelated parallel machine and 5) the corresponding production planning and scheduling methods for each model. By combining the concept of ATP, this architecture can not only provide resource planning for networked-manufacturing system, but also offer quick response and promise to customer requests.

Production Planning Considering Transfer Lot Size

2010 ◽  
Vol 44-47 ◽  
pp. 552-556
Author(s):  
Zhi Cong Zhang ◽  
Kai Shun Hu ◽  
Hui Yu Huang ◽  
Shuai Li
Keyword(s):  
Production Planning ◽  
Performance Measures ◽  
Lot Sizing ◽  
Mixed Integer ◽  
Production Plan ◽  
Lot Size ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling ◽  
Lot Sizing Problem ◽  
Plan Change

Traditional methods conduct production planning and scheduling separately and solve transfer lot sizing problem between these two steps. Unfortunately, this may result in infeasibility in planning and scheduling. We take into account transfer lot size in production planning to obtain the consistency and to eliminate the gap between planning and real production. We present the detailed Transfer Lot-Based Model with mixed integer programming. Experiments show that performance measures of a production plan change remarkably with increasing of transfer lot size.

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