Single-Machine Sustainable Production Planning to Minimize Total Energy Consumption and Total Completion Time Using a Multiple Objective Genetic Algorithm

2012 ◽  
Vol 59 (4) ◽  
pp. 585-597 ◽  
Author(s):  
Mehmet Bayram Yildirim ◽  
Gilles Mouzon
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Total Energy ◽  
Production Planning ◽  
Single Machine ◽  
Completion Time ◽  
Sustainable Production ◽  
Total Completion Time ◽  
Multiple Objective ◽  
Total Energy Consumption

Optimizing the production scheduling of a single machine to minimize total energy consumption costs

2014 ◽  
Vol 67 ◽  
pp. 197-207 ◽  
Author(s):  
Fadi Shrouf ◽  
Joaquin Ordieres-Meré ◽  
Alvaro García-Sánchez ◽  
Miguel Ortega-Mier
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Single Machine ◽  
Production Scheduling ◽  
Total Energy Consumption

scholarly journals Simulation-Based Genetic Algorithm towards an Energy-Efficient Railway Traffic Control

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Daniel Tuyttens ◽  
Hongying Fei ◽  
Mohand Mezmaz ◽  
Jad Jalwan
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Total Energy ◽  
Traffic Control ◽  
Energy Efficient ◽  
Energy Utilization ◽  
Utilization Rate ◽  
Total Energy Consumption ◽  
Railway Traffic ◽  
Mode Control

The real-time traffic control has an important impact on the efficiency of the energy utilization in the modern railway network. This study is aimed to develop an energy-efficient railway traffic control solution for any specified railway. In other words, it is expected to define suitable driving profiles for all the trains running within a specified period through the targeted network with an objective to minimize their total energy consumption. How to optimize the train synchronization so as to benefit from the energy regenerated by electronic braking is also considered in this study. A method based on genetic algorithm and empirical single train driving strategies is developed for this objective. Six monomode strategies and one multimode strategy are tested and compared with the four scenarios extracted from the Belgian railway system. The results obtained by simulation show that the multi-mode control strategy overcomes the mono-mode control strategies with regard to global energy consumption, while there is no firm relation between the utilization rate of energy regenerated by dynamic braking operations and the reduction of total energy consumption.

scholarly journals Research on Machining Workshop Batch Scheduling Incorporating the Completion Time and Non-Processing Energy Consumption Considering Product Structure

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6079
Author(s):  
Nailiang Li ◽  
Caihong Feng
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Completion Time ◽  
Level Structure ◽  
Optimal Schedule ◽  
Product Structure ◽  
Collaborative Optimization ◽  
Batch Scheduling ◽  
Practical Significance ◽  
Total Energy Consumption

Energy-saving scheduling is a well-known issue in the manufacturing system. The flexibility of the workshop increases the difficulty of scheduling. In the workshop schedule, considering the collaborative optimization of multi-level structure product production and energy consumption has certain practical significance. The process sequence of parts and components should be consistent with the assembly sequence. Additionally, the non-production energy consumption (NPEC) (such as the energy consumption of workpiece handling, equipment standby, and workpiece conversion) generated by the auxiliary machining operations, which make up the majority of the total energy consumption, should not be ignored. A sub-batch priority is set according to the upper and lower coupling relationship in the product structure. A bi-objective batch scheduling model that minimizes the total energy consumption and the total completion time is developed, and the multi-objective gray wolf optimizer (MOGWO) is employed as the solution to obtain the optimal schedule scheme. A case study is performed to demonstrate the potential possibilities concerning NPEC in regard to reducing the total energy consumption and to show the effectiveness of the algorithm. Compared with the traditional optimization model, the joint optimization of NPEC and PEC can reduce the energy consumption of standby and handling by 9.95% and 22.28%, respectively.

Energy savings potential of new aeration system: Full scale trials

2012 ◽  
Vol 7 (4) ◽  
Author(s):  
A. Lazić ◽  
V. Larsson ◽  
Å. Nordenborg
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Total Energy ◽  
Energy Savings ◽  
Treatment Plant ◽  
Full Scale ◽  
Total Energy Consumption ◽  
Aeration System ◽  
Fine Bubble ◽  
Aeration Control

The objective of this work is to decrease energy consumption of the aeration system at a mid-size conventional wastewater treatment plant in the south of Sweden where aeration consumes 44% of the total energy consumption of the plant. By designing an energy optimised aeration system (with aeration grids, blowers, controlling valves) and then operating it with a new aeration control system (dissolved oxygen cascade control and most open valve logic) one can save energy. The concept has been tested in full scale by comparing two treatment lines: a reference line (consisting of old fine bubble tube diffusers, old lobe blowers, simple DO control) with a test line (consisting of new Sanitaire Silver Series Low Pressure fine bubble diffusers, a new screw blower and the Flygt aeration control system). Energy savings with the new aeration system measured as Aeration Efficiency was 65%. Furthermore, 13% of the total energy consumption of the whole plant, or 21 000 €/year, could be saved when the tested line was operated with the new aeration system.

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