Abstract
The multi-objective multiple traveling salesman problem (MmTSP) is a generalization of the classical multi-objective traveling salesman problem. In this paper, a formulation of the MmTSP, which considers the weighted sum of the total traveling costs of all salesmen and the highest traveling cost of any single salesman, is proposed. An estimation of distribution algorithm (EDA) based on restricted Boltzmann machine is used for solving the formulated problem. The EDA is developed in the decomposition framework of multi-objective optimization. Due to the limitation of EDAs in generating a wide range of solutions, the EDA is hybridized with the evolutionary gradient search. Simulation studies are carried out to examine the optimization performances of the proposed algorithm on MmTSP with different number of objective functions, salesmen and problem sizes.
| Original language | English |
|---|---|
| Title of host publication | 2012 IEEE Congress on Evolutionary Computation |
| Publisher | IEEE |
| ISBN (Print) | 978-1-4673-1509-8 |
| DOIs | |
| Publication status | Published - Jun 2012 |
| Externally published | Yes |
| Event | 2012 IEEE Congress on Evolutionary Computation, CEC 2012 - Brisbane, QLD, Australia Duration: 10 Jun 2012 → 15 Jun 2012 |
Conference
| Conference | 2012 IEEE Congress on Evolutionary Computation, CEC 2012 |
|---|---|
| Place | Australia |
| City | Brisbane, QLD |
| Period | 10/06/12 → 15/06/12 |
Research Keywords
- Decomposition
- estimation of distribution algorithm
- evolutionary gradient search
- hybrid multi-objective optimization
- multiple traveling salesman problem
- restricted Boltzmann machine
Fingerprint
Dive into the research topics of 'A hybrid estimation of distribution algorithm for solving the multi-objective multiple traveling salesman problem'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver