Efficient neighborhood search for the Probabilistic Pickup and Delivery Travelling Salesman Problem

Networks ◽  
2005 ◽  
Vol 45 (4) ◽  
pp. 195-198 ◽  
Author(s):  
Patrizia Beraldi ◽  
Gianpaolo Ghiani ◽  
Gilbert Laporte ◽  
Roberto Musmanno
Keyword(s):  
Travelling Salesman Problem ◽  
Neighborhood Search ◽  
Pickup And Delivery ◽  
Travelling Salesman

Heuristic algorithm for the Split-Demand One-Commodity Pickup-and-Delivery Travelling Salesman Problem

2018 ◽  
Vol 97 ◽  
pp. 1-17 ◽  
Author(s):  
Hipólito Hernández-Pérez ◽  
Juan José Salazar-González ◽  
Beatriz Santos-Hernández
Keyword(s):  
Heuristic Algorithm ◽  
Travelling Salesman Problem ◽  
Pickup And Delivery ◽  
Travelling Salesman

scholarly journals EFFICIENT METAHEURISTIC ALGORITHMS FOR THE MULTI-STRIPE TRAVELLING SALESMAN PROBLEM

2020 ◽  
Vol 36 (3) ◽  
pp. 233-250
Author(s):  
Ban Ha Bang
Keyword(s):  
Quadratic Assignment Problem ◽  
Travelling Salesman Problem ◽  
Computation Time ◽  
Metaheuristic Algorithms ◽  
Neighborhood Search ◽  
Quadratic Assignment ◽  
Travelling Salesman ◽  
Local Optima ◽  
Benchmark Instances ◽  
Main Components

The Multi-stripe Travelling Salesman Problem (Ms-TSP) is an extension of the Travelling Salesman Problem (TSP). In the \textit{q}-stripe TSP with $q \geq 1$, the objective function sums the costs for travelling from one customer to each of the next \textit{q} customers along the tour. The resulting \textit{q}-stripe TSP generalizes the TSP and forms a special case of the Quadratic Assignment Problem. To solve medium and large size instances, a metaheuristic algorithm is proposed. The proposed algorithm has two main components, which are construction and improvement phases. The construction phase generates a solution using Greedy Randomized Adaptive Search Procedure (GRASP) while the optimization phase improves the solution with several variants of Variable Neighborhood Search, both coupled with a technique called Shaking Technique to escape from local optima. In addition, Adaptive Memory is integrated into our algorithms to balance between the diversification and intensification. To show the efficiency of our proposed metaheuristic algorithms, we extensively experiment on benchmark instances. The results indicate that the developed algorithms can produce efficient and effective solutions at a reasonable computation time.

The probabilistic pickup-and-delivery travelling salesman problem

2019 ◽  
Vol 121 ◽  
pp. 313-323 ◽  
Author(s):  
Enrique Benavent ◽  
Mercedes Landete ◽  
Juan-José Salazar-González ◽  
Gregorio Tirado
Keyword(s):  
Travelling Salesman Problem ◽  
Pickup And Delivery ◽  
Travelling Salesman
Sign in / Sign up

Export Citation Format

Share Document