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.

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.

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