Optimization Problems with Color-Induced Budget Constraints

2016 ◽  
pp. 189-200
Author(s):  
Corinna Gottschalk ◽  
Hendrik Lüthen ◽  
Britta Peis ◽  
Andreas Wierz
Keyword(s):  
Optimization Problems ◽  
Budget Constraints

Optimization problems with color-induced budget constraints

2017 ◽  
Vol 36 (3) ◽  
pp. 861-870
Author(s):  
Corinna Gottschalk ◽  
Hendrik Lüthen ◽  
Britta Peis ◽  
Andreas Wierz
Keyword(s):  
Optimization Problems ◽  
Budget Constraints

Comparison of Meta-heuristic Algorithms on Benchmark Functions

2019 ◽  
Vol 2 (3) ◽  
pp. 508-517
Author(s):  
FerdaNur Arıcı ◽  
Ersin Kaya
Keyword(s):  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Differential Evolution Algorithm ◽  
Population Based ◽  
Time Interval ◽  
Bee Colony ◽  
Different Characteristics

Optimization is a process to search the most suitable solution for a problem within an acceptable time interval. The algorithms that solve the optimization problems are called as optimization algorithms. In the literature, there are many optimization algorithms with different characteristics. The optimization algorithms can exhibit different behaviors depending on the size, characteristics and complexity of the optimization problem. In this study, six well-known population based optimization algorithms (artificial algae algorithm - AAA, artificial bee colony algorithm - ABC, differential evolution algorithm - DE, genetic algorithm - GA, gravitational search algorithm - GSA and particle swarm optimization - PSO) were used. These six algorithms were performed on the CEC’17 test functions. According to the experimental results, the algorithms were compared and performances of the algorithms were evaluated.

Large Scale Plant Optimization Problems

1988 ◽  
Author(s):  
Paul Cronin ◽  
Harry Woerde ◽  
Rob Vasbinder
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Plant Optimization
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