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Proceedings ArticleDOI

Computation of lower bounds for a multiple depot, multiple vehicle routing problem with motion constraints

TLDR
A method is developed to compute lower bounds to this path planning problem by relaxing some of the constraints and posing it as a standard multiple traveling salesmen problem using the convexity property of the length of such paths.
Abstract
In this paper, the problem of planning paths for a collection of vehicles passing through a set of targets is considered. Each vehicle starts at a specified location (called a depot) and it is required that each target be on the path of at least one vehicle. Every vehicle has a motion constraint and the path of each vehicle must satisfy that constraint. In this article, we developed a method to compute lower bounds to this path planning problem by relaxing some of the constraints and posing it as a standard multiple traveling salesmen problem. For those problem instances where the distance between every pair of targets is at least 4 units, another method is developed to compute a lower bound using the convexity property of the length of such paths. The proposed bounds are numerically corroborated.

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Citations
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Journal ArticleDOI

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

TL;DR: This article describes the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning, and provides insights into widespread and emerging modeling approaches to civil applications of UAVs.
Journal ArticleDOI

Algorithms for Heterogeneous, Multiple Depot, Multiple Unmanned Vehicle Path Planning Problems

TL;DR: In this paper, a branch-and-cut algorithm is proposed to find an optimal path for each vehicle starting and ending at its respective depot such that each target is visited at least once by some vehicle, the vehicle-target constraints are satisfied, and the sum of the length of the paths for all the vehicles is minimized.
Journal ArticleDOI

A vehicle routing problem arising in unmanned aerial monitoring

TL;DR: This study investigates a routing problem in which UAVs monitor a set of areas with different accuracy requirements, which is a variant of the classical vehicle routing problem (VRP), and a tabu search metaheuristic is developed for the problem.
Journal ArticleDOI

On Tightly Bounding the Dubins Traveling Salesman's Optimum

TL;DR: This article presents the first systematic procedure for developing tight lower bounds for the Dubins Traveling Salesman Problem and addresses the fundamental issue of how to find an optimal solution to the problem.
Proceedings ArticleDOI

Dubins paths through a sequence of points: Lower and upper bounds

TL;DR: Novel tight lower bounding algorithms are presented in this article by relaxing some of the heading angle constraints at the target points by solving variants of an optimization problem called the Dubins interval problem between two points where the heading angles at the points are constrained to be within a specified interval.
References
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Book

Integer and Combinatorial Optimization

TL;DR: This chapter discusses the Scope of Integer and Combinatorial Optimization, as well as applications of Special-Purpose Algorithms and Matching.
Journal ArticleDOI

The Lagrangian Relaxation Method for Solving Integer Programming Problems

TL;DR: This paper is a review of Lagrangian relaxation based on what has been learned in the last decade and has led to dramatically improved algorithms for a number of important problems in the areas of routing, location, scheduling, assignment and set covering.
Journal ArticleDOI

An effective implementation of the Lin–Kernighan traveling salesman heuristic

TL;DR: An implementation of the Lin–Kernighan heuristic, one of the most successful methods for generating optimal or near-optimal solutions for the symmetric traveling salesman problem (TSP), is described.
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