Author
Gitae Kim
Bio: Gitae Kim is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Markov decision process & Supply chain. The author has an hindex of 3, co-authored 3 publications receiving 197 citations.
Papers
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TL;DR: The state of the art of City VRP is identified, the core challenging issues are highlighted, and some potential research area in this field that have remained underexplored are suggested.
Abstract: Lately, the Vehicle Routing Problem (VRP) in the city, known as City VRP, has gained popularity with its importance in city logistics. Similar to city logistics, City VRP mainly differs from conventional VRP in terms of the stakeholders involved, namely the shipper, carrier, resident, and administrator. Accordingly, this paper surveys the City VRP literature categorized by stakeholders and summarizes the constraints, models, and solution methods for VRP in urban cities. City VRPs are also analyzed based on the problem of interest considered by the stakeholders and the corresponding models that have been proposed in response. Through this review, we identify the state of the art of City VRP, highlight the core challenging issues, and suggest some potential research area in this field that have remained underexplored.
140 citations
TL;DR: A Markov decision process model is proposed to solve the dynamic vehicle routing problem (DVRP) with nonstationary stochastic travel times under traffic congestion and adopts a rollout-based approach to the solution, using approximate dynamic programming to avoid the curse of dimensionality.
Abstract: This paper proposes a dynamic vehicle routing problem (DVRP) model with nonstationary stochastic travel times under traffic congestion. Depending on the traffic conditions, the travel time between two nodes, particularly in a city, may not be proportional to distance and changes both dynamically and stochastically over time. Considering this environment, we propose a Markov decision process model to solve this problem and adopt a rollout-based approach to the solution, using approximate dynamic programming to avoid the curse of dimensionality. We also investigate how to estimate the probability distribution of travel times of arcs which, reflecting reality, are considered to consist of multiple road segments. Experiments are conducted using a real-world problem faced by Singapore logistics/delivery company and authentic road traffic information.
80 citations
TL;DR: The progressive hedging method is extended to solve the multi-period newsvendor model problem efficiently, and the problem is formulated as a multi-stage stochastic programming model with integer recourse decisions.
52 citations
Cited by
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TL;DR: A state-of-the-art survey of the Benders Decomposition algorithm, emphasizing its use in combinatorial optimization and introducing a taxonomy of algorithmic enhancements and acceleration strategies based on the main components of the algorithm.
506 citations
TL;DR: An up-to-date review of perishable inventory models, but also of the joint key topics of publications from January 2012 until December 2015 in the research area of deteriorating inventory models is given.
206 citations
Book•
01 Jan 2001
TL;DR: In this article, the authors model city logistics with ITS and present a model for vehicle routing and scheduling with ITS, where demand and supply models and impact models are modelled and the location of logistics terminals are modeled.
Abstract: Chapter headings: Introduction. Modelling city logistics. City logistics with ITS. Demand and supply models. Impact models. Vehicle routing and scheduling. Vehicle routing and scheduling with ITS. Location of logistics terminals. Future perspectives. References. Index.
193 citations
01 Jan 2005
190 citations