Amortized efficiency of list update and paging rules
Communications of the ACM
Maximizing job completions online
Journal of Algorithms
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
Algorithms for the on-line quota traveling salesman problem
Information Processing Letters
Theoretical Computer Science - Approximation and online algorithms
Online Routing Problems: Value of Advanced Information as Improved Competitive Ratios
Transportation Science
The online Prize-Collecting Traveling Salesman Problem
Information Processing Letters
On the power of lookahead in on-line server routing problems
Theoretical Computer Science
A Stochastic and Dynamic Vehicle Routing Problem with Time Windows and Customer Impatience
Mobile Networks and Applications
Online deadline scheduling with preemption penalties
Computers and Industrial Engineering
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We consider the online version of the traveling salesman problem, where instances are not known in advance. Requests are released over time regardless whether the server is en route or not. This problem has been described as online TSP. Current literature about online TSP assumes that each request becomes known at its release time and will always remain active. We model the customers' waiting psychology and service preparation time into the online TSP with the objective to serve as many requests as possible. More specifically, each request has a disclosure time before accepting service at its release time, and a deadline, which is no bigger than its release time plus the travel time from origin to its position. We give lower bounds for the competitive ratios, online algorithms, and quantify the influence of advanced information on competitive ratios.