Group search optimizer: a nature-inspired meta-heuristic optimization algorithm with its results, variants, and applications

2020 ◽  
Author(s):  
Laith Abualigah
Keyword(s):  
Optimization Algorithm ◽  
Heuristic Optimization ◽  
Group Search

scholarly journals Buyer Inspired Meta-Heuristic Optimization Algorithm

2020 ◽  
Vol 10 (1) ◽  
pp. 194-219 ◽  
Author(s):  
Sanjoy Debnath ◽  
Wasim Arif ◽  
Srimanta Baishya
Keyword(s):  
Optimization Algorithm ◽  
Optimization Technique ◽  
Statistical Test ◽  
Heuristic Optimization ◽  
Product Choice ◽  
Exploration And Exploitation ◽  
The Social ◽  
Engineering Problems ◽  
The Mean

AbstractNature inspired swarm based meta-heuristic optimization technique is getting considerable attention and established to be very competitive with evolution based and physical based algorithms. This paper proposes a novel Buyer Inspired Meta-heuristic optimization Algorithm (BIMA) inspired form the social behaviour of human being in searching and bargaining for products. In BIMA, exploration and exploitation are achieved through shop to shop hoping and bargaining for products to be purchased based on cost, quality of the product, choice and distance to the shop. Comprehensive simulations are performed on 23 standard mathematical and CEC2017 benchmark functions and 3 engineering problems. An exhaustive comparative analysis with other algorithms is done by performing 30 independent runs and comparing the mean, standard deviation as well as by performing statistical test. The results showed significant improvement in terms of optimum value, convergence speed, and is also statistically more significant in comparison to most of the reported popular algorithms.

scholarly journals A Hybrid Genetic Wind Driven Heuristic Optimization Algorithm for Demand Side Management in Smart Grid

Energies ◽  
2017 ◽  
Vol 10 (3) ◽  
pp. 319 ◽  
Author(s):  
Nadeem Javaid ◽  
Sakeena Javaid ◽  
Wadood Abdul ◽  
Imran Ahmed ◽  
Ahmad Almogren ◽  
...  
Keyword(s):  
Smart Grid ◽  
Optimization Algorithm ◽  
Demand Side Management ◽  
Heuristic Optimization ◽  
Demand Side

scholarly journals Deterministic oscillatory search: a new meta-heuristic optimization algorithm

Sadhana ◽  
2017 ◽  
Vol 42 (6) ◽  
pp. 817-826 ◽  
Author(s):  
N Archana ◽  
R Vidhyapriya ◽  
Antony Benedict ◽  
Karthik Chandran
Keyword(s):  
Optimization Algorithm ◽  
Heuristic Optimization

Shuffled shepherd optimization method: a new Meta-heuristic algorithm

2020 ◽  
Vol 37 (7) ◽  
pp. 2357-2389 ◽  
Author(s):  
Ali Kaveh ◽  
Ataollah Zaerreza
Keyword(s):  
Heuristic Algorithm ◽  
Optimization Algorithm ◽  
Design Methodology ◽  
Optimization Method ◽  
Optimization Process ◽  
Heuristic Optimization ◽  
Benchmark Problems ◽  
Content Type

Purpose This paper aims to present a new multi-community meta-heuristic optimization algorithm, which is called shuffled shepherd optimization algorithm (SSOA). In this algorithm. Design/methodology/approach The agents are first separated into multi-communities and the optimization process is then performed mimicking the behavior of a shepherd in nature operating on each community. Findings A new multi-community meta-heuristic optimization algorithm called a shuffled shepherd optimization algorithm is developed in this paper and applied to some attractive examples. Originality/value A new metaheuristic is presented and tested with some classic benchmark problems and some attractive structures are optimized.

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