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A decision support system for optimizing dynamic courier routing operations
Affiliation:1. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;2. Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong;3. Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong;1. Department of Electronics Convergence Engineering, Wonkwang University, 344-2, Shinyong-Dong, Iksan, Jeonbuk 570-749, South Korea;2. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2G7, Canada;3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland;1. Department of Systems Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Avenu, Kowloon Tong, Hong Kong;2. Centre for Systems Informatics Engineering, City University of Hong Kong, 83 Tat Chee Avenu, Kowloon Tong, Hong Kong;3. School of Management, Hefei University of Technology, Hefei, Box 270, Hefei 230009, Anhui, PR China;4. Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, Box 270, Hefei 230009, Anhui, PR China
Abstract:
In this paper, we propose a prototype of a decision support system (DSS) that integrates a hybrid neighborhood search algorithm to solve the offline and online routing problems arising in courier service. In the dynamic operational environment of courier service, new customer orders and order cancellations continually arrive over time and thus disrupt the optimal routing schedule that was originally designed. This calls for the real-time re-optimization of routes. As service level is sensitive to whether allowable service time intervals are wide or narrow, it is valuable to study how adjustable and flexible time windows influence the courier service efficiency in a dynamic environment. To capture these dynamic features, a dynamic vehicle routing problem (DVRP) that simultaneously considers new customer orders and order cancellations is investigated in this study. Meanwhile, fuzzy time windows are formulated in the DVRP model to quantify the service level and explore the service efficiency. To tackle the new problem, we propose a competitive hybrid neighborhood search heuristic for (re)optimizing the offline and online routes. Numerical computational experiments and the comparison with results from Lingo show that our algorithm is capable of re-optimizing dynamic problems effectively and accurately in a very short time. The proposed model and algorithms are able to enhance courier service level without further expense of a longer traveling distance or a larger number of couriers.
Keywords:Dynamic vehicle routing  Decision support system  Variable Neighborhood Search  Fuzzy logic  Courier service
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