Adaptive heuristic search algorithm for discrete variables based multi-objective optimization

2013 ◽  
Vol 48 (4) ◽  
pp. 821-836 ◽  
Author(s):  
Long Tang ◽  
Hu Wang ◽  
Guangyao Li ◽  
Fengxiang Xu
Keyword(s):  
Heuristic Search ◽  
Search Algorithm ◽  
Discrete Variables ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Heuristic Search Algorithm ◽  
Adaptive Heuristic

scholarly journals On Algorithmic Descriptions and Software Implementations for Multi-objective Optimisation: A Comparative Study

2020 ◽  
Vol 1 (5) ◽  
Author(s):  
Shahin Rostami ◽  
Ferrante Neri ◽  
Kiril Gyaurski
Keyword(s):  
Heuristic Search ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Multi Objective ◽  
The Past ◽  
Heuristic Search Algorithm ◽  
Software Implementations ◽  
Software Platforms ◽  
Algorithmic Structure ◽  
Real World Problems

Abstract Multi-objective optimisation is a prominent subfield of optimisation with high relevance in real-world problems, such as engineering design. Over the past 2 decades, a multitude of heuristic algorithms for multi-objective optimisation have been introduced and some of them have become extremely popular. Some of the most promising and versatile algorithms have been implemented in software platforms. This article experimentally investigates the process of interpreting and implementing algorithms by examining multiple popular implementations of three well-known algorithms for multi-objective optimisation. We observed that official and broadly employed software platforms interpreted and thus implemented the same heuristic search algorithm differently. These different interpretations affect the algorithmic structure as well as the software implementation. Numerical results show that these differences cause statistically significant differences in performance.

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