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Title:
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A NEW PARALLEL HYBRID MULTIOBJECTIVE ANT
COLONY ALGORITHM BASED ON OPENMP |
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Author(s):
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Imen Ben Mansour, Ines Alaya and Moncef Tagina |
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ISBN:
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978-989-8704-24-5 |
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Editors:
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Hans Weghorn |
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Year:
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2020 |
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Edition:
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Single |
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Keywords:
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Parallel Metaheuristic, Threads, OpenMP, Ant Colony Optimization, Multiobjective Optimization, The Augmented
Weighted Tchebycheff Method |
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Type:
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Full |
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First Page:
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19 |
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Last Page:
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26 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Parallel computing constitutes a growing area of interest in solving many complex combinatorial optimization problems.
This paper presents a parallel implementation of a hybrid ant colony optimization metaheuristic for the multiobjective
knapsack problem using the OpenMP framework. The hybrid algorithm coupled a MultiObjective Ant Colony
Optimization (MOACO) algorithm with Tchebycheff based Local Search (TLS) procedure. The parallelization main idea
is defined as assuming a shared-memory based on threads in which the initialization phase begins with a single thread
called the master thread and executed sequentially. Afterward, a parallel region is defined where many threads are
created, each one of them executing its own copy of the proposed ant colony algorithm independently. The threads
cooperate through sharing a global archive holding all non-dominated solutions found so far. Experimental results show a
significant efficiency of the solutions returned over the sequential implementation. |
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