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Chen Kim Heng
Researcher at Agency for Science, Technology and Research
Publications - 6
Citations - 170
Chen Kim Heng is an academic researcher from Agency for Science, Technology and Research. The author has contributed to research in topics: Evolutionary computation & Vehicle routing problem. The author has an hindex of 4, co-authored 6 publications receiving 118 citations.
Papers
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Journal ArticleDOI
City Vehicle Routing Problem (City VRP): A Review
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.
Proceedings ArticleDOI
Towards adaptive weight vectors for multiobjective evolutionary algorithm based on decomposition
Siwei Jiang,Liang Feng,Dazhi Yang,Chen Kim Heng,Yew-Soon Ong,Allan N. Zhang,Puay Siew Tan,Zhihua Cai +7 more
TL;DR: The core idea of FV-MOEA/D is to periodically adjust weight vectors based on solutions in the proposed archive, in which convergence and diversity are maintained by maximizing hypervolume.
Book ChapterDOI
Multi-objective Heterogeneous Capacitated Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery for Urban Last Mile Logistics
TL;DR: The proposed model is solved through two proposed methods that are based on exact methods and a number of insights into the MoHCVRP-TWSPD problem are provided.
Proceedings ArticleDOI
Adaptive indicator-based evolutionary algorithm for multiobjective optimization problems
Siwei Jiang,Liang Feng,Chen Kim Heng,Quoc Chinh Nguyen,Yew-Soon Ong,Allan N. Zhang,Puay Siew Tan +6 more
TL;DR: A new version of I BEA1 (labeled as IBEA2 hereafter) is proposed to adaptively adjust parameter κ for solving various MOPs and the core idea of IBEa2 is to adapt parameter λ for the purpose of selecting the subset of offspring solutions with the maximum hypervolume into the next population.
Proceedings ArticleDOI
Application of route flexibility in data-starved vehicle routing problem with time windows
Chen Kim Heng,Quoc Chinh Nguyen,Siwei Jiang,Puay Siew Tan,Abhishek Gupta,Bingshui Da,Yew-Soon Ong +6 more
TL;DR: An evolutionary algorithm is presented that in the absence of data on travel time uncertainty, provides a decision maker with a collection of solutions, each with a corresponding level of trade-off between total travel distance and solution robustness.