scholarly journals Using of Metaheuristic Water Cycle Algorithm in order to Determine Optimal Crop Cultivation across of Genetic Algorithm and linear programming (Case Study: Varamin Irrigation Network)

2019 ◽  
Vol 23 (03) ◽  
Keyword(s):  
Genetic Algorithm ◽  
Linear Programming ◽  
Water Cycle ◽  
Irrigation Network ◽  
Water Cycle Algorithm ◽  
Crop Cultivation

Optimal Operation of Multireservoir Systems by Enhanced Water Cycle Algorithm

2019 ◽  
Vol 7 (1) ◽  
pp. 27-43
Author(s):  
Yanjun Kong ◽  
Yadong Mei ◽  
Weinan Li ◽  
Ben Yue ◽  
Xianxun Wang
Keyword(s):  
Water Cycle ◽  
Water System ◽  
System Size ◽  
Optimal Operation ◽  
Test Functions ◽  
Water Cycle Algorithm ◽  
Adaptive Parameter ◽  
Fitness Value ◽  
Better Than

In this article, an enhanced water cycle algorithm (EWCA) is proposed and applied to optimize the operation of multireservoir systems. Three improvements have been made to the water cycle algorithm (WCA). They refer to high-quality initial solutions obtained by the chaos-based method, balancing of exploration of streams using a dynamic adaptive parameter, and dynamic variation of sub-water system size using the fitness value of rivers. For the purpose of verifying the improvements, three typical benchmark functions were selected as test functions. It has shown that EWCA performs better than WCA and water cycle algorithm with evaporation rate (ER-WCA). And then these three algorithms were also applied to optimize the operation of a multireservoir system with complex constrains as the case study. By comparing the results, it is found that the EWCA has higher ability to find a feasible solution in a narrow searching space. The effectiveness of the improvements is confirmed.

scholarly journals Metaheuristic Optimization of Ammonia Factor as a Eutrophication Pollution Emission Descriptor for Trophic State Stability

2020 ◽  
Vol 11 (10) ◽  
pp. 460-470
Author(s):  
Ronnie S. Concepcion II ◽  
◽  
Sandy C. Lauguico ◽  
Argel A. Bandala ◽  
Jonnel D. Alejandrino ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Optimum Condition ◽  
Trophic State ◽  
Water Cycle ◽  
Fitness Function ◽  
Important Indicator ◽  
Water Cycle Algorithm ◽  
Fitness Score ◽  
Nutrient Imbalance ◽  
Ph Level

Aquaponic toxicity relies on the combinations of its pollution parameters that are dissolved in water and emitted in air. Ammonia is considered as an important indicator affecting aquaculture species, water nutrient imbalance and air pollution. Trophic state of aquatic body is measured by ammonia. In this study, the suitability of metaheuristic models, namely, genetic algorithm, simulated annealing, water cycle algorithm, enhanced vibrating particles system and particle swarm optimization, in determining the optimum condition of ammonia factor for providing minimal toxicity and oligotrophication was determined by varying its corresponding hyperparameters. The parameters that were optimized are water temperature and pH level. These parameters significantly affect ammonia factor that is an essential contributor to eutrophication. The optimized genetic algorithm yielded the practical-ideal fitness function value for ammonia factor as to compare with other optimized metaheuristics based on optimizing time. It selected the 50 fittest individuals based on their fitness score with the rate of 0.2 and proceeds to recombination process to extract characteristics from parent chromosomes with crossover rate of 0.8. The mutation rate of 0.01 was injected to form diversity and to test if the global solution was attained. The tournament size is 4 and the reproduction elite count is 2.5. The best condition of the ammonia factor was extracted when the number of generations has been reached. The GA results showed that the optimum condition for ammonia factor that will prevent eutrophication and provide ecological balance in aquaponic system needs a temperature of 29.254 °C and pH of 7.614.

Prioritizing the Surgical Waiting List-Cosine Consistency Index: An Optimized Framework for Prioritizing Surgical Waiting List

2020 ◽  
Vol 10 (12) ◽  
pp. 2876-2892
Author(s):  
Hemant Petwal ◽  
Rinkle Rani
Keyword(s):  
Genetic Algorithm ◽  
Evaporation Rate ◽  
Water Cycle ◽  
Pairwise Comparison ◽  
Waiting List ◽  
Consistency Index ◽  
Real Patient ◽  
Pairwise Comparison Matrix ◽  
Water Cycle Algorithm ◽  
Comparison Matrix

This paper aims to examine patient prioritization challenges faced by surgeons attending to patients awaiting surgery and proposes a decision-making framework named PSWL-CCI to prioritize patients in the surgical waiting list. The proposed framework deals with two critical issues: One, to prioritize patients from the surgical waiting list. Two, to refine and optimize cosine consistency index (CCI) of inconsistent pairwise comparison matrix (PCM) and obtain consistent priorities. The judgment of surgeons on identified parameters in the term of rating helps in determining priorities from the surgical waiting list. The cosine maximization method (CM), along with the analytic hierarchy process (AHP), is used to evaluate the resulting priority. To improve inconsistent pairwise comparison matrix (PCM), a novel hybrid algorithm HMWCA (Hybrid modified water cycle algorithm), is proposed and incorporated in PSWL-CCI. The proposed algorithm exploits the feature of three traditional algorithms, namely the evaporation-based water cycle algorithm (ER-WCA), genetic algorithm, and 2-opt heuristic. In this paper, the concept of salt concentration and absorption introduced into the evaporation rate (ER) that extends ER-WCA to a modified water cycle algorithm (MWCA). MWCA iteratively modifies the entries in PCM until PCM is optimized. The genetic algorithm helps MWCA to determine the evaporation rate and enhance the rate of convergence. The 2-OPT algorithm improvises the optimal solution. The proposed algorithm is tested with different datasets, and the improved CCI values are validated through paired sample t-test. Finally, the proposed PSWL-CCI framework is validated through a case study of a real patient dataset from an orthopedic surgery department of a multispecialty hospital in India. The experimental results obtained in this study reveal that the proposed methodology and algorithms significantly improve the CCI values, thus generating optimum priorities for the patients of the surgical waiting list.

Water Cycle Algorithm for Parameters Estimation of Solar Photovoltaic Model

2019 ◽  
Vol 7 (3) ◽  
pp. 117
Author(s):  
Abeer Shaban Omar ◽  
Hany M. Hasanien ◽  
Ahmed Al-Durra ◽  
Walid H. Abd El-Hameed
Keyword(s):  
Water Cycle ◽  
Parameters Estimation ◽  
Solar Photovoltaic ◽  
Water Cycle Algorithm

Developing Schedule With Linear Programming (Case Study: STTF II Project Komplek Sukamukti Banjaran)

2020 ◽  
Vol 4 (02) ◽  
pp. 34-45
Author(s):  
Naufal Dzikri Afifi ◽  
Ika Arum Puspita ◽  
Mohammad Deni Akbar
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Project Scheduling ◽  
Time Limit ◽  
Minimum Time ◽  
Service Cost ◽  
Trade Off ◽  
Overtime Work ◽  
The Cost

Shift to The Front II Komplek Sukamukti Banjaran Project is one of the projects implemented by one of the companies engaged in telecommunications. In its implementation, each project including Shift to The Front II Komplek Sukamukti Banjaran has a time limit specified in the contract. Project scheduling is an important role in predicting both the cost and time in a project. Every project should be able to complete the project before or just in the time specified in the contract. Delay in a project can be anticipated by accelerating the duration of completion by using the crashing method with the application of linear programming. Linear programming will help iteration in the calculation of crashing because if linear programming not used, iteration will be repeated. The objective function in this scheduling is to minimize the cost. This study aims to find a trade-off between the costs and the minimum time expected to complete this project. The acceleration of the duration of this study was carried out using the addition of 4 hours of overtime work, 3 hours of overtime work, 2 hours of overtime work, and 1 hour of overtime work. The normal time for this project is 35 days with a service fee of Rp. 52,335,690. From the results of the crashing analysis, the alternative chosen is to add 1 hour of overtime to 34 days with a total service cost of Rp. 52,375,492. This acceleration will affect the entire project because there are 33 different locations worked on Shift to The Front II and if all these locations can be accelerated then the duration of completion of the entire project will be effective

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