Optimization Method Based on Genetic Evolution for Multiple-Stage Coordinate Mining of Multiple Mining Areas with same Coal

2013 ◽  
Vol 807-809 ◽  
pp. 2460-2469
Author(s):  
Qiang Zeng ◽  
Ze Bin Zhang ◽  
Zu Qiang Xiong ◽  
De Quo Xiong
Keyword(s):  
Optimization Model ◽  
Mathematical Optimization ◽  
Optimization Method ◽  
Great Difficulty ◽  
Simplified Model ◽  
Genetic Evolution ◽  
Total Sale ◽  
Mining Areas ◽  
Mathematical Optimization Model

Aiming at the multiple-stage coordinate mining problem for multiple mining areas with same coal, an optimization method based on genetic evolution is proposed. Firstly, a mathematical optimization model with the objective to maximize the total sale of synthetic coal is established. Then, the model is simplified to another mathematical optimization model with the objective to maximize price of synthetic coal of each stage because of the great difficulty to resolve the model. Thirdly, a genetic algorithm for coordinate mining of multiple mining areas is presented and designed to resolve the simplified model. Finally, the effectiveness of the proposed method is validated by case study.

scholarly journals Optimization of Pump Start-Up Depth in Drainage Pumping Station Based on SWMM and PSO

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1002 ◽  
Author(s):  
Hao Wang ◽  
Xiaohui Lei ◽  
Soon-Thiam Khu ◽  
Lixiang Song
Keyword(s):  
Operating Time ◽  
Mathematical Optimization ◽  
Optimization Method ◽  
Storm Water Management Model ◽  
Pumping Station ◽  
Pumping Stations ◽  
Start Up ◽  
Study Results ◽  
Mathematical Optimization Model

The pumps in multistage drainage pumping stations are often subject to frequent start-up and shutoffs during operation because of unreasonable start-up depths of the pumps; this will reduce the service lives of the pumps. To solve this problem, an optimization method for minimizing pump start-up and shutoff times is proposed. In this method, the operation of pumps in pumping station was optimized by constructing a mathematical optimization model. The storm water management model (SWMM) and particle swarm optimization (PSO) method were used to solve the problem and the optimal start-up depth of each pump is obtained. Nine pumping stations in Beijing were selected as a case study and this method was applied for multistage pumping station optimization and single pumping station optimization in the case study. Results from the case study demonstrate that the multistage pumping station optimization acquired a small number of pump start-up/shutoff times, which were from 8 to 114 in different rainfall scenarios. Compared with the multistage pumping station optimization, the single pumping station optimization had a bigger number of pump start-up/shutoff times, which were from 1 to 133 times, and the pump operating time was also longer, from 72 min to 7542 min. Therefore, the multistage pumping station optimization method was more suitable to reduce the frequency of pump start-up/shutoffs.

Optimization Method for Robust Continuous Parameter Design in the Target-being-Best Based on Genetic Evolution

2014 ◽  
Vol 1049-1050 ◽  
pp. 1272-1280
Author(s):  
Qiang Zeng ◽  
Ling Shen ◽  
Ze Bin Zhang
Keyword(s):  
Genetic Algorithm ◽  
Theoretical Calculation ◽  
Optimization Model ◽  
Optimization Method ◽  
Parameter Design ◽  
Genetic Evolution ◽  
Quality Loss ◽  
Average Quality ◽  
Continuous Parameter

Aiming at the problem of robust continuous parameter design in the Target-being-best, in which the output value can be obtained by theoretical calculation, an optimization method based on genetic evolution is proposed. Firstly, the researched problem is described mathematically and an optimization model is established with the objective to minimize the average quality loss of a sample. Secondly, the optimization method based on genetic evolution for the researched problem is proposed. Thirdly, the genetic algorithm for robust continuous parameter design in the Target-being-best is presented and designed. Finally, the effectiveness of the proposed method is validated by case study.

scholarly journals A Mathematical Optimization Model for Locating Telecenters

2012 ◽  
Vol 03 (03) ◽  
pp. 251-263 ◽  
Author(s):  
Morteza Tabatabaie Shourijeh ◽  
Mohammad Kermanshah ◽  
Amir Reza Mamdoohi ◽  
Ardeshir Faghri ◽  
Khaled Hamad
Keyword(s):  
Optimization Model ◽  
Mathematical Optimization ◽  
Mathematical Optimization Model

scholarly journals Optimal Semi-Competitive Intermediation Networks

2020 ◽  
Vol 20 (5) ◽  
pp. 81-94
Author(s):  
Amelia Bădică ◽  
Costin Bădică ◽  
Maria Ganzha ◽  
Mirjana Ivanović ◽  
Marcin Paprzycki
Keyword(s):  
Optimization Model ◽  
Numerical Optimization ◽  
Autonomous Agents ◽  
Mathematical Optimization ◽  
Optimal Strategies ◽  
Directed Acyclic Graphs ◽  
Pricing Strategies ◽  
Computational Results ◽  
Acyclic Graphs ◽  
Mathematical Optimization Model

AbstractIn this work we address the problem of optimizing collective profitability in semi-competitive intermediation networks defined as augmented directed acyclic graphs. Network participants are modeled as autonomous agents endowed with private utility functions. We introduce a mathematical optimization model for defining pricing strategies of network participants. We employ welfare economics aiming to maximize the Nash social welfare of the intermediation network. The paper contains mathematical results that theoretically prove the existence of such optimal strategies. We also discuss computational results that we obtained using a nonlinear convex numerical optimization package.

scholarly journals Optimizing Bus Line Based on Metro-Bus Integration

2020 ◽  
Vol 12 (4) ◽  
pp. 1493 ◽  
Author(s):  
Junjun Wei ◽  
Kejun Long ◽  
Jian Gu ◽  
Qingling Ju ◽  
Piao Zhu
Keyword(s):  
Resource Allocation ◽  
Optimization Model ◽  
Geographical Location ◽  
Optimization Method ◽  
Line Number ◽  
Competition And Cooperation ◽  
Travel Efficiency ◽  
Geographical Space ◽  
Metro System

Metros are usually built and added on the basis of a completed bus network in Chinese cities. After the metro construction, it is faced with the problem of how to adjust and optimize the original bus lines based on the new metro system. This research mainly proposes a bus line optimization method based on bus and metro integration. In the consideration of the geographical space, the cooperation and competition relationship between bus and metro lines is qualitatively introduced according to the geographical location and service range of metro (800 m radius) and bus (500 m radius) stations. The competition and cooperation indexes are applied to define the co-opetition relationship between bus and metro lines. The bus line optimization model is constructed based on the co-opetition coefficient and Changsha Metro Line Number 2 is chosen as a case study to verify the optimization model. The results show that the positive competition, efficient cooperation, and travel efficiency between metro and bus has been significantly enhanced after optimization. Moreover, this paper provides a reasonable reference for public transport network planning and resource allocation.

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