Abstract—In this paper, we propose a framework for employing opposition-based learning to assist evolutionary algorithms in solving discrete and combinatorial optimization proble...
The generalized traveling salesman problem (GTSP) is an NPhard problem that extends the classical traveling salesman problem by partitioning the nodes into clusters and looking fo...
The traveling salesman problem with time windows is known to be a really difficult benchmark for optimization algorithms. In this paper, we are interested in the minimization of th...
The Traveling Salesman Problem (TSP) is still one of the most researched topics in computational mathematics, and we introduce a variant of it, namely the study of the closed k-wa...
Grady Bullington, Linda Eroh, Ralucca Gera, Steven...
Abstract— In this work we focus on mission planning problems in scenarios in which a carrier vehicle, typically slow but with virtually infinite range, and a carried vehicle, wh...
This paper explores a novel setting for compressed sensing (CS) in which the sampling trajectory length is a critical bottleneck and must be minimized subject to constraints on th...
In this paper we propose a novel algorithm for opinion summarization that takes account of content and coherence, simultaneously. We consider a summary as a sequence of sentences ...
In the Traveling Salesman Problem with Pickup and Delivery (TSPPD) a single vehicle must serve a set of customer requests, each defined by an origin location where a load must be...
We extend the work of Letchford (2000) by introducing a new class of valid inequalities for the traveling salesman problem, called the generalized domino-parity (GDP) constraints....
William J. Cook, Daniel G. Espinoza, Marcos Goycoo...
In this paper we review the exact algorithms proposed in the last three decades for the solution of the vehicle routing problem with time windows (VRPTW). The exact algorithms for...