Solving constrained traveling salesman problems by genetic algorithms*
Source abstract
Abstract
Abstract Three kinds of constrained traveling salesman problems (TSP) arising from application problems, namely the open route TSP, the end-fixed TSP, and the path-constrained TSP, are proposed. The corresponding approaches based on modified genetic algorithms (GA) for solving these constrained TSPs are presented. Numerical experiments demonstrate that the algorithm for the open route TSP shows its advantages when the open route is required, the algorithm for the end-fixed TSP can deal with route optimization with constraint of fixed ends effectively, and the algorithm for the path-constraint could benefit the traffic problems where some cities cannot be visited from each other.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Vehicle Routing Optimization Methods · Robotic Path Planning Algorithms · Metaheuristic Optimization Algorithms Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (7)
Show source-provided references
1. LiangY.C.Solving traveling salesman problems by genetic algorithms Progress in Natural Science 2003132135135
2. KatayamaK.The efficiency of hybrid mutation genetic algorithm for the travelling salesman problem Mathematical and Computer Modeling 20003110–12197197
3. MoonC.An efficient generic algorithm for the traveling salesman problem with precedence constraints European Journal of Operational Research 20021403606606
4. TannenbaumP. Excursions in Modern Mathematics4th ed. Prentice HallNJ2000
5. KusiakA.Modeling and solving the flexible forging module scheduling problem Engineering Optimization 198712111
6. SavelsberghM.W.P.The general pickup and delivery problem Transportation Science 19952911717
7. MingozziA.Dynamic programming strategies for the TSP with time windows and precedence constraints Operations Research 1997453365365