Shuffled shepherd optimization method: a new Meta-heuristic algorithm. Issue 7 (11th March 2020)

• Record Type: Journal Article
• Authors: Kaveh, Ali; Zaerreza, Ataollah
• Is Part Of: Engineering computations. Volume 37:Issue 7(2020)
• Page Start: 2357
• Page End: 2389
• Publication Date: 2020-03-11
• Subjects: Shuffled shepherd optimization algorithm -- Sheep -- Shepherd -- Meta-heuristic -- Optimization -- Mathematical bench mark -- Truss structures optimization; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-10-2019-0481
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : 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.