Optimizing monthly ecological flow regime by a coupled fuzzy physical habitat simulation–genetic algorithm method

2021 ◽  
Author(s):  
Mahdi Sedighkia ◽  
Asghar Abdoli ◽  
Bithin Datta
Keyword(s):  
Genetic Algorithm ◽  
Flow Regime ◽  
Physical Habitat ◽  
Ecological Flow ◽  
Habitat Simulation ◽  
Genetic Algorithm Method

Research on the Ecological Water Demand Based on Physical Habitat Simulation Model

2014 ◽  
Vol 1022 ◽  
pp. 376-379
Author(s):  
Jun Xian Chen ◽  
Rui Zhi Qiao ◽  
Wen Hua Li ◽  
Xin Wen
Keyword(s):  
Life Cycle ◽  
Water Demand ◽  
Southwest China ◽  
Aquatic Organisms ◽  
Habitat Model ◽  
Environmental Benefits ◽  
Physical Habitat ◽  
Ecological Water Demand ◽  
Ecological Flow ◽  
Habitat Simulation

A basin in Southwest China is selected as an example for ecological water demand calculation to obtain the ecological flow required for the survival of typical creatures within the watershed by solving the physical habitat model. The implementation of ecological operation can better meet the two fish suitable ecological needs for each life cycle, and is of great significance for fish conservation. Results indicate that the implementation of ecological operation has tremendous ecological environmental benefits and great significance for the protection of aquatic organisms.

Habitat Elements in River Basin Management and Planning

1987 ◽  
Vol 19 (9) ◽  
pp. 19-29 ◽  
Author(s):  
Edwin E. Herricks ◽  
Maria I. Braga
Keyword(s):  
Water Quality ◽  
River Basin ◽  
River Basin Management ◽  
The United States ◽  
Physical Habitat ◽  
Basin Management ◽  
Habitat Analysis ◽  
Management Procedures ◽  
Habitat Simulation ◽  
Flow Quantity

Comprehensive river basin management mast move beyond narrowly focused programs dealing with water quantity or water quality. A more comprehensive approach to river basin management recognizes that both flow quantity and water quality can be summarized as habitat measures. A number of well developed physical habitat analysis and prediction procedures are presently available. Several computerized systems available from the U.S.Fish and Wildlife Service (Habitat Suitability Index - HSI and PHysical HABitat SIMulation - PHABSIM) provide macrohabitat definition. We have developed a water quality based habitat component which operates effectively for general analysis. With an emphasis on site specific management in the United States, the macrohabitat definition procedures may not meet all river basin management and planning requirements. This paper reviews the results of research which characterizes microhabitat in streams and rivers and provides a valuable extension to basin management procedures.

scholarly journals The Use of a Simulation Model for High-Runner Strategy Implementation in Warehouse Logistics

2020 ◽  
Vol 12 (23) ◽  
pp. 9818
Author(s):  
Gabriel Fedorko ◽  
Vieroslav Molnár ◽  
Nikoleta Mikušová
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Optimization Problem ◽  
Software Tool ◽  
Time Saving ◽  
General Validity ◽  
Resistance Function ◽  
Genetic Algorithm Method ◽  
Working Day ◽  
Enterprise Logistics

This paper examines the use of computer simulation methods to streamline the process of picking materials within warehouse logistics. The article describes the use of a genetic algorithm to optimize the storage of materials in shelving positions, in accordance with the method of High-Runner Strategy. The goal is to minimize the time needed for picking. The presented procedure enables the creation of a software tool in the form of an optimization model that can be used for the needs of the optimization of warehouse logistics processes within various types of production processes. There is a defined optimization problem in the form of a resistance function, which is of general validity. The optimization is represented using the example of 400 types of material items in 34 categories, stored in six rack rows. Using a simulation model, a comparison of a normal and an optimized state is realized, while a time saving of 48 min 36 s is achieved. The mentioned saving was achieved within one working day. However, the application of an approach based on the use of optimization using a genetic algorithm is not limited by the number of material items or the number of categories and shelves. The acquired knowledge demonstrates the application possibilities of the genetic algorithm method, even for the lowest levels of enterprise logistics, where the application of this approach is not yet a matter of course but, rather, a rarity.

Genetic Algorithm and its Application in Optimization of Frequency Selective Surface

2010 ◽  
Vol 143-144 ◽  
pp. 1046-1050
Author(s):  
Jing Yu Han ◽  
Wang Qun ◽  
Chuan You Li ◽  
Zhang Hong Tang ◽  
Mei Wu Shi
Keyword(s):  
Genetic Algorithm ◽  
Cost Function ◽  
Electroless Plating ◽  
Genetic Basis ◽  
Optimization Method ◽  
Frequency Selective Surface ◽  
Test System ◽  
Genetic Algorithm Method ◽  
Frequency Selective ◽  
Test Result

In this paper, a new genetic algorithm method to optimize the frequency selective surface(FSS) is presented. The optimization speed and definition are promoted by limiting the parameter range and changing the genetic basis. A new cost function is introduced to optimize the multi-frequency of FSS by multi-object optimization (MO). The cirque element was optimized by the optimization method, fabricated by the selective electroless plating on fabric and measured by the arch test system. Test result proves the simulated result coincide with measured result. Result shows that it’s possible to realize different optimizations based on the various applying by this method.

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