DSM Using Fish Swarm Optimization and Harmony Search Algorithm Using HEMS in Smart Grid

2017 ◽  
pp. 525-535
Author(s):  
Shahzeb Haider ◽  
Hafiz Muhammad Faisal ◽  
Zenab Amin ◽  
Haq Nawaz ◽  
Kaleem Akram ◽  
...  
Keyword(s):  
Smart Grid ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Swarm Optimization

scholarly journals The Buttressed Walls Problem: An Application of a Hybrid Clustering Particle Swarm Optimization Algorithm

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 862 ◽  
Author(s):  
José García ◽  
José V. Martí ◽  
Víctor Yepes
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Particle Swarm ◽  
Retaining Walls ◽  
Harmony Search Algorithm ◽  
Swarm Optimization ◽  
Practical Applications ◽  
Reinforced Earth

The design of reinforced earth retaining walls is a combinatorial optimization problem of interest due to practical applications regarding the cost savings involved in the design and the optimization in the amount of CO 2 emissions generated in its construction. On the other hand, this problem presents important challenges in computational complexity since it involves 32 design variables; therefore we have in the order of 10 20 possible combinations. In this article, we propose a hybrid algorithm in which the particle swarm optimization method is integrated that solves optimization problems in continuous spaces with the db-scan clustering technique, with the aim of addressing the combinatorial problem of the design of reinforced earth retaining walls. This algorithm optimizes two objective functions: the carbon emissions embedded and the economic cost of reinforced concrete walls. To assess the contribution of the db-scan operator in the optimization process, a random operator was designed. The best solutions, the averages, and the interquartile ranges of the obtained distributions are compared. The db-scan algorithm was then compared with a hybrid version that uses k-means as the discretization method and with a discrete implementation of the harmony search algorithm. The results indicate that the db-scan operator significantly improves the quality of the solutions and that the proposed metaheuristic shows competitive results with respect to the harmony search algorithm.

scholarly journals Comparisional Investigation of Load Dispatch Solutions with TLBO

2017 ◽  
Vol 7 (6) ◽  
pp. 3246
Author(s):  
DSNM Rao ◽  
Niranjan Kumar
Keyword(s):  
Particle Swarm Optimization ◽  
Teaching And Learning ◽  
Search Algorithm ◽  
Harmony Search ◽  
Heuristic Method ◽  
Harmony Search Algorithm ◽  
Optimization Techniques ◽  
The Other ◽  
Economic Load Dispatch ◽  
Swarm Optimization

This paper discusses economic load dispatch Problem is modeled with non-convex functions. These are problem are not solvable using a convex optimization techniques. So there is a need for using a heuristic method. Among such methods Teaching and Learning Based Optimization (TLBO) is a recently known algorithm and showed promising results. This paper utilized this algorithm to provide load dispatch solutions. Comparisons of this solution with other standard algorithms like Particle Swarm Optimization (PSO), Differential Evolution (DE) and Harmony Search Algorithm (HSA). This proposed algorithm is applied to solve the load dispatch problem for 6 unit and 10 unit test systems along with the other algorithms. This comparisional investigation explored various merits of TLBO with respect to PSO, DE, and HAS in the field economic load dispatch.

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