Search Results for author:
Found 6 papers, 2 papers with code
Progressive Focus Search for the Static and Stochastic VRPTW with both Random Customers and Reveal Times
We show how to compute the expected cost of a priori solutions, in pseudo-polynomial time, for this recourse strategy.
A Hybrid Genetic Algorithm for the Traveling Salesman Problem with Drone
This paper addresses the Traveling Salesman Problem with Drone (TSP-D), in which a truck and drone are used to deliver parcels to customers.
The Static and Stochastic VRPTW with both random Customers and Reveal Times: algorithms and recourse strategies
Like the SS-VRP introduced by Bertsimas (1992), we search for optimal first stage routes for a fleet of vehicles to handle a set of stochastic customer demands, i. e., demands are uncertain and we only know their probabilities.
On the Min-cost Traveling Salesman Problem with Drone
We solve a TSP to generate route for truck and propose a mixed integer programming (MIP) formulation with different profit functions to build route for drone.
On the Min-cost Traveling Salesman Problem with Drone
The first algorithm (TSP-LS) was adapted from the approach proposed by Murray and Chu (2015), in which an optimal TSP solution is converted to a feasible TSP-D solution by local searches.
A Multistage Stochastic Programming Approach to the Dynamic and Stochastic VRPTW - Extended version
We introduce a new decision rule, called Global Stochastic Assessment (GSA) rule for the DS-VRPTW, and we compare it with existing decision rules, such as MSA.
