An optimization model for refinery production scheduling

2002 ◽  
Vol 78 (3) ◽  
pp. 255-270 ◽  
Author(s):  
Maud Göthe-Lundgren ◽  
Jan T. Lundgren ◽  
Jan A. Persson
Keyword(s):  
Optimization Model ◽  
Production Scheduling ◽  
Refinery Production

Refinery production scheduling toward Industry 4.0

2018 ◽  
Vol 0 (0) ◽  
pp. 0 ◽  
Author(s):  
Marcel JOLY ◽  
Darci ODLOAK ◽  
MarioY. MIYAKE ◽  
Brenno C. MENEZES ◽  
Jeffrey D. KELLY
Keyword(s):  
Production Scheduling ◽  
Industry 4.0 ◽  
Refinery Production

scholarly journals Multiobjective Joint Optimization of Production Scheduling and Maintenance Planning in the Flexible Job-Shop Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jianfei Ye ◽  
Huimin Ma
Keyword(s):  
Decision Making ◽  
Optimization Model ◽  
Preventive Maintenance ◽  
Production Scheduling ◽  
Job Shop ◽  
Joint Optimization ◽  
Planning Problem ◽  
Flexible Job Shop ◽  
Maintenance Planning ◽  
Joint Decision

In order to solve the joint optimization of production scheduling and maintenance planning problem in the flexible job-shop, a multiobjective joint optimization model considering the maximum completion time and maintenance costs per unit time is established based on the concept of flexible job-shop and preventive maintenance. A weighted sum method is adopted to eliminate the index dimension. In addition, a double-coded genetic algorithm is designed according to the problem characteristics. The best result under the circumstances of joint decision-making is obtained through multiple simulation experiments, which proves the validity of the algorithm. We can prove the superiority of joint optimization model by comparing the result of joint decision-making project with the result of independent decision-making project under fixed preventive maintenance period. This study will enrich and expand the theoretical framework and analytical methods of this problem; it provides a scientific decision analysis method for enterprise to make production plan and maintenance plan.

scholarly journals Carbon-Efficient Production Scheduling of a Bioethanol Plant Considering Diversified Feedstock Pelletization Density: A Case Study

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1189
Author(s):  
Xinchao Li ◽  
Xin Jin ◽  
Shan Lu ◽  
Zhe Li ◽  
Yue Wang ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Optimization Model ◽  
Production Scheduling ◽  
Raw Materials ◽  
Future Research ◽  
Efficient Production ◽  
Emission Model ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling ◽  
Total Profit

This paper presents a dual-objective optimization model for production scheduling of bioethanol plant with carbon-efficient strategies. The model is developed throughout the bioethanol production process. Firstly, the production planning and scheduling of the bioethanol plant’s transportation, storage, pretreatment, and ethanol manufacturing are fully considered. Secondly, the carbon emissions in the ethanol manufacturing process are integrated into the model to form a dual-objective optimization model that simultaneously optimizes the production plan and carbon emissions. The effects of different biomass raw materials with optional pelletization density and pretreatment methods on production scheduling are analyzed. The influence of demand and pretreatment cost on selecting a pretreatment method and total profit is considered. A membership weighted method is developed to solve the dual-objective model. The carbon emission model and economic model are integrated into one model for analysis. An example is given to verify the effectiveness of the optimization model. At the end of the paper, the limitation of this study is discussed to provide directions for future research.

Research on Optimization Method of Real-Time Available Resources for Dynamic Scheduling

2013 ◽  
Vol 427-429 ◽  
pp. 2650-2655
Author(s):  
J.H. Ge ◽  
W.Y. Li ◽  
Y.P. Shi ◽  
T.Q. Duan ◽  
Y.Q. Chen
Keyword(s):  
Real Time ◽  
Dynamic Property ◽  
Optimization Model ◽  
Production Scheduling ◽  
Dynamic Scheduling ◽  
Optimization Method ◽  
Dynamic Feedback ◽  
Resource Information ◽  
Global Dynamic ◽  
Available Resources

Aimed at the real-time request of dynamic scheduling to product resource, an optimization method of parallel dynamic chain real-time available resources was put forward. Proceed from real-time tracing of resource information influencing scheduling tasks dynamic property, established a resource informations real-time tracing back and optimization model, which used module and parallel process mechanism to different kinds of real-time traced back resource information. The mechanism processed global dynamic feedback tracing for every module and optimized available resources primarily, on this basis, graded the primary available resources and gave a real-time candidate resource set. Through one example of one gear production scheduling, the methods validity was tested.

scholarly journals Production Scheduling Optimization of Prefabricated Building Components Based on DDE Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Chunguang Chang ◽  
Mengyao Han
Keyword(s):  
Optimization Model ◽  
Production Scheduling ◽  
Precast Concrete ◽  
Optimal Solution ◽  
Production Costs ◽  
Process Time ◽  
Concrete Members ◽  
Hybrid Optimization Model ◽  
Continuous Work ◽  
Process Constraints

At present, the prefabricated construction industry is in a situation of increasing types of prefabricated components and generally high production costs. A hybrid optimization model considering continuity and discreteness for the production of fabricated concrete members is established to minimize production costs through the analysis of the production characteristics of precast concrete members. Under the premise of fully considering the staffing constraints, process constraints, construction period constraints, process constraints, and special process time limits for component production, the production arrangement and staffing of the components are rationalized and optimized. A discrete differential evolution (DDE) algorithm is introduced for such NP-hard problems. The double genetic chromosome coding mode and the active scheduling decoding method are adopted. Based on the improved POX (Precedence Operation Crossover) cross-evolution method, the global evolution operation is carried out, and an interchange-based local search method and continuous work penalty mechanism are designed to find the global optimal solution. The experimental results verify the practicality and effectiveness of the optimization model and algorithm.

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