A new optimization algorithm for the vehicle routing problem with time windows
Operations Research
An overview of vehicle routing problems
The vehicle routing problem
Approximating the Throughput of Multiple Machines in Real-Time Scheduling
SIAM Journal on Computing
Approximation Results for Kinetic Variants of TSP
ICAL '99 Proceedings of the 26th International Colloquium on Automata, Languages and Programming
Approximation Algorithms for the Job Interval Selection Problem and Related Scheduling Problems
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
Approximation Algorithms for Orienteering and Discounted-Reward TSP
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Approximation algorithms for deadline-TSP and vehicle routing with time-windows
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
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We consider the following variant of the Vehicle Routing Problem that we call the Pickup and Delivery for Moving Objects (PDMO) problem, motivated by robot navigation: The input to the problem consists of n products, each of which moves on a predefined path with a fixed constant speed, and a robot arm of capacity one. In each round, the robot arm grasps and delivers one product to its original position. The goal of the problem is to find a collection of tours such that the robot arm grasps and delivers as many products as possible. In this paper we prove the following results: (i) If the products move on broken lines with at least one bend, then the PDMO is MAXSNP-hard, and (ii) it can be approximated with ratio two. However, (iii) if we impose the “straight line without bend” restriction on the motion of every product, then the PDMO becomes tractable.