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19
Dynamic pickup and delivery problems
, 2009
"... In the last decade, there has been an increasing body of research in dynamic vehicle routing problems. This article surveys the subclass of those problems called dynamic pickup and delivery problems, in which objects or people have to be collected and delivered in real time. It discusses some genera ..."
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Cited by 45 (0 self)
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In the last decade, there has been an increasing body of research in dynamic vehicle routing problems. This article surveys the subclass of those problems called dynamic pickup and delivery problems, in which objects or people have to be collected and delivered in real time. It discusses some general issues as well as solution strategies.
Dynamic Vehicle Routing for Robotic Systems
, 2010
"... Recent years have witnessed great advancements in ..."
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Cited by 34 (10 self)
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Recent years have witnessed great advancements in
Competitive Analysis of a Dispatch Policy for a Dynamic MultiPeriod Routing Problem
"... We analyze a simple and natural online algorithm (dispatch policy) for a dynamic multiperiod uncapacitated routing problem, in which at the beginning of each time period a set of orders arrive that have to be served either in that time period or in the next. The objective of the problem is to minim ..."
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We analyze a simple and natural online algorithm (dispatch policy) for a dynamic multiperiod uncapacitated routing problem, in which at the beginning of each time period a set of orders arrive that have to be served either in that time period or in the next. The objective of the problem is to minimize the average routing cost per time period. We show that the competitive ratio of this online algorithm for instances with customers on the nonnegative real line is 3 2. 1
Online Traveling Salesman Problems with Service Flexibility
, 2011
"... The Traveling Salesman Problem (TSP) is a wellknown combinatorial optimization problem. We are concerned here with online versions of this problem defined on metric spaces. One novel aspect in the paper is the introduction of a sound theoretical model to incorporate “yesno ” decisions on which req ..."
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The Traveling Salesman Problem (TSP) is a wellknown combinatorial optimization problem. We are concerned here with online versions of this problem defined on metric spaces. One novel aspect in the paper is the introduction of a sound theoretical model to incorporate “yesno ” decisions on which requests to serve, together with an online strategy to visit the accepted requests. In order to do so, we assume that there is a penalty for not serving a request. Requests for visit of points in the metric space are revealed over time to a server, initially at a given origin, who must decide in an online fashion which requests to serve in order to minimize the time to serve all accepted requests plus the sum of the penalties associated with the rejected requests. We first look at the special case of the nonnegative real line. After providing a polynomial time algorithm for the offline version of the problem, we propose and prove the optimality of a 2competitive polynomial time online algorithm based on reoptimization approaches. We also consider the impact of advanced information (lookahead) on this optimal competitive ratio. We then consider the generalizations of these results to the case of the real line. We show that the previous algorithm can be extended to an optimal 2competitive online algorithm. Finally we consider the case of a general metric space and propose an original ccompetitive online algorithm, where c = √ 17+5 4 ≈ 2.28. We also give a polynomialtime (1.5ρ + 1)competitive online algorithm which uses a polynomialtime ρapproximation for the offline problem.
Can agents measure up? A comparative study of an agentbased and online optimization approach for a drayage problem with uncertainty
, 2009
"... ..."
extension to classical Vehicle Routing Problems. We
"... customers may both receive and send goods, are an ..."
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Optimization in dynamic environments
, 2011
"... This survey presents major results and issues related to the study of NPO problems in dynamic environments, that is, in settings where instances are allowed to undergo some modifications over time. In particular, the survey focuses on two complementary frameworks. The first one is the reoptimization ..."
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This survey presents major results and issues related to the study of NPO problems in dynamic environments, that is, in settings where instances are allowed to undergo some modifications over time. In particular, the survey focuses on two complementary frameworks. The first one is the reoptimization framework, where an instance I that is already solved undergoes some local perturbation. The goal is then to make use of the information provided by the initial solution to compute a new solution. The second framework is probabilistic optimization, where the instance to optimize is not fully known at the time when a solution is to be proposed, but results from a determined Bernoulli process. Then, the goal is to compute a solution with optimal expected value.
Myopic and Anticipated Planning in Stochastic Swap Container Management
, 2010
"... Abstract � We introduce a dynamic and stochastic transportation problem consisting of two subproblems. For parcel transportation in hubandspoke networks, swap containers are used to carry out hubtohub shipments. This constitutes a pickup and delivery problem on the operational level. On the tact ..."
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Abstract � We introduce a dynamic and stochastic transportation problem consisting of two subproblems. For parcel transportation in hubandspoke networks, swap containers are used to carry out hubtohub shipments. This constitutes a pickup and delivery problem on the operational level. On the tactical level, empty swap containers are balanced over the hubnetwork in order to match the stochastic demand of empty swap containers in future periods. This twolevel problem is referred to as Stochastic Swap Container Problem. In this paper, mathematical models and integrated solution strategies considering stochastic arrival patterns for shipments are developed. We present a comprehensive computational study comparing myopic and anticipating planning approaches.