Abstract
Algorithm Development Environment for Permutation-based problems (ADEP) is a software environment for configuring meta-heuristics for solving combinatorial optimization problems. This paper describes the key features of ADEP and how the environment was used to generate a Memetic Algorithm (MA) solution for Hamiltonian Cycle Problems (HCP). The effectiveness of the MA algorithm is demonstrated through computer simulations and its performance is compared with backtracking and other heuristic techniques such as Simulated Annealing, Tabu Search, and Ant Colony Optimization.
Recommended Citation
X. S. Chen et al., "A Memetic Algorithm Configured Via a Problem Solving Environment for the Hamiltonian Cycle Problems," Proceedings of the IEEE Congress on Evolutionary Computation, 2007, Institute of Electrical and Electronics Engineers (IEEE), Sep 2007.
The definitive version is available at https://doi.org/10.1109/CEC.2007.4424821
Meeting Name
IEEE Congress on Evolutionary Computation, 2007
Department(s)
Electrical and Computer Engineering
Sponsor(s)
Singapore Technologies (Firm)
Keywords and Phrases
Evolutionary Computation; Graph Theory; Mathematics Computing; Optimization
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2007 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Sep 2007
