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Outsourcing Decisions for Truck Fleets with Quantity Discounts for Continuous Working Shifts |
LI Shu-qin1, YANG Bin1, HU Zhi-hua1,2, MING Hui1, ZHOU Zhen1 |
1. Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China;
2. School of Economics and Management, Tongji University, Shanghai 200092, China |
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Abstract To cope with the capacity limitations of enterprise's own transport fleet for container transport and the increasing competitive pressure, considering the operating costs and the demand uncertainty, an outsourcing decision-making problem for truck fleet with quantity discounts for continuous working shifts is presented. From the perspective of competition and social-effects analysis, we suggest an extended vehicle routing problem with time windows (VRPTW) vehicle scheduling model. The model minimizes costs and provides an evaluation system with minimal mileage and carbon emissions. By adjusting quantity-discount rules and task time windows, our model can be used to provide outsourcing solutions for different combinations of continuous working shifts. We also discuss the influence of other parameter settings on the decision schemes. Finally, we verify both the model and the algorithm using a simulation experiment. The experimental results show that using quantity discounts for fleet outsourcing decisions for different combinations of continuous working shifts improves both vehicle utilization and social benefits. We also highlight new research opportunities based on these results.
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Received: 21 December 2013
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Fund:Supported by the National Natural Science Foundation of China (NO.71101088, No.71171129);the National Social Science Foundation of China (No.11&ZD169);the China Postdoctoral Science Foundation (No.2011M500077);the Doctoral Fund of Ministry of Education of China (No.20113121120002);and the Innovation Project Fund of Graduate Student of Shanghai Maritime University (No.wk2012039) |
Corresponding Authors:
LI Shu-qin, llishuqin@163.com
E-mail: llishuqin@163.com
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[1] LI Yi-hua, LI Xia-miao, WANG Zhong-wei, et al, Vehicle Routing Problem in Container Port Based on Outsourcing[J]. Systems Engineering, 2009, 27(10):14-20. (in Chinese)
[2] TAN K C, CHEW Y H, LEE L H. A Hybrid Multi-objective Evolutionary Algorithm for Solving Truck and Trailer Vehicle Routing Problems[J]. European Journal of Operational Research, 2006, 172(3):855-885.
[3] FENG B, FAN Z, LI Y. A Decision Method for Supplier Selection in Multi-service Outsourcing[J]. International Journal of Production Economics, 2011, 132(2):240-250.
[4] FISCHER T, GEHRING H. Planning Vehicle Transshipment in a Seaport Automobile Terminal Using a Multi-agent System[J]. European Journal of Operational Research, 2005, 166(1):726-740.
[5] LEE L H, TAN K C, OU K, et al. Vehicle Capacity Planning System:A Case Study on Vehicle Routing Problem with Time Windows[J]. IEEE Transactions on Systems, Man, and Cybernetics, 2003, 33(2):169-178.
[6] ELIIYI D T, ORNEK A, KARAKÜTÜK S S. A Vehicle Scheduling Problem with Fixed Trips and Time Limitations[J]. International Journal of Production Economics, 2009, 117(1):150-161.
[7] PUREZA V, MORABITOA R, REIMANN M. Vehicle Routing with Multiple Deliverymen:Modeling and Heuristic Approaches for the VRPTW[J]. European Journal of Operational Research, 2012, 218(3):636-647.
[8] ZÄPFEL G, BÖGL M. Multi-period Vehicle Routing and Crew Scheduling with Outsourcing Options[J]. International Journal of Production Economics, 2008, 113(2):980-996.
[9] KRITIKOS M N, IOANNOU G. The Balanced Cargo Vehicle Routing Problem with Time Windows[J]. International Journal of Production Economics, 2010, 123(1):42-51.
[10] MOON L, LEE J H, SEONG J. Vehicle Routing Problem with Time Windows Considering Overtime and Outsourcing Vehicles[J]. Expert Systems with Applications, 2012, 39(18):13202-13213.
[11] LEE S, TURNER J, DASKIN M S, et al. Improving Fleet Utilization for Carriers by Interval Scheduling[J]. European Journal of Operational Research, 2012, 218(1):261-269.
[12] MANSINI R, SAVELSBERGH M W P, TOCCHELLA B. The Supplier Selection Problem with Quantity Discounts and Truckload Shipping[J]. Omega, 2012, 40(4):445-455.
[13] MUNSON C L, HU J. Incorporating Quantity Discounts and Their Inventory Impacts into the Centralized Purchasing Decision[J]. European Journal of Operational Research, 2010, 201(2):581-592.
[14] NIU Zhi-yong, HUANG Pei, GAO Wei-he. The Research on Quantity Discount Model of Channel Based on Quantal Response Equilibrium and Experiment[J]. Journal of Management Science, 2010, 23(2):45-51. (in Chinese)
[15] TSAI W H, LEE K C, LIU J Y, et al. A Mixed Activity-based Costing Decision Model for Green Airline Fleet Planning under the Constraints of the European Union Emissions Trading Scheme[J]. Energy, 2012, 39(1):218-226. |
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