TLHSA and SACA: two heuristic algorithms for two variant VRP models

Vehicle routing problem (VRP) is a classical combinatorial optimization problem. Under this problem, we focus on two variant models which better capture the real-world scenes: multiple-orders pickup and delivery problem with time-bound window (MOPDPTW) and dynamic vehicle routing problem with time w...

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Vydáno v:Journal of combinatorial optimization Ročník 44; číslo 4; s. 2996 - 3022
Hlavní autoři: Cai, Xuhong, Jiang, Li, Guo, Songhu, Huang, Hejiao, Du, Hongwei
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.11.2022
Springer Nature B.V
Témata:
Algorithms
Ant colony optimization
Combinatorial analysis
Combinatorics
Convex and Discrete Geometry
Heuristic methods
Mathematical Modeling and Industrial Mathematics
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Route planning
Search algorithms
Theory of Computation
Vehicle routing
Windows (intervals)
DVRPTW
Two-layers heuristic search
MOPDPTW
Pheromone updating
Dynamical algorithm framework
ISSN:1382-6905, 1573-2886
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Popis
Shrnutí:Vehicle routing problem (VRP) is a classical combinatorial optimization problem. Under this problem, we focus on two variant models which better capture the real-world scenes: multiple-orders pickup and delivery problem with time-bound window (MOPDPTW) and dynamic vehicle routing problem with time window (DVRPTW). To tackle MOPDPTW, a two-layers heuristic search algorithm is proposed. The inner layer of proposed algorithm searches possible solutions in global and sends them to the outer layer to find local optimal solution. In order to solve DVRPTW, a general dynamical algorithm framework is designed to tackle the dynamic nature of the problem. Then based on ant colony algorithm, we propose several effective strategies called pheromone preserving mechanism, pheromone updating based on important solution components and parameter self-adaptive adjustment, aiming to improve the solution construction process by ants. We validate our two algorithms on different standard benchmarks and the results indicate that our proposed algorithms are competitive and effective compared with the state-of-the-art approaches.
Bibliografie:ObjectType-Article-1
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ISSN:1382-6905
1573-2886
DOI:10.1007/s10878-021-00831-0