COLD CHAIN MANAGEMENT BY USING VEHICLE ROUTING PROBLEM WITH TIME WINDOWS AND UNCERTAIN TRAVEL TIMES
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Abstract
This research aimed to 3 objectives 1) To analyze and evaluate the impact of travel time uncertainty on the efficiency of cold chain systems, 2) To develop a two-phase vehicle routing approach for distributing goods in the Bangkok Metropolitan Region and its vicinity as well as for inter-provincial deliveries and 3) To compare the outcomes of the developed system with the actual routing data used by case study of organization. This research is used a mix method by the quantitative part focus on a mathematical model of the vehicle routing problem with time windows (VRPTW), which is categorized as NP-Hard problem and applied the Tabu Search (TS) metaheuristic to obtain near optimal solutions. The model is programed and simulated using MATLAB with real operational data from a case study company serving 91 customers. The qualitative part involved comparing the simulation results with the actual routing decisions designed by employees with more than 20 years of practical experience. The results showed that 1) In Bangkok and vicinity, the TS approach reduced the number of vehicles from 5 to 4 decreased total travel time from 1,331 minutes to 857 minutes (Reduction of 35.61%) and lowered the total travel distance by 13.42% and 2) Provincial areas, the number of vehicles is reduced from 21 to 18 and the total travel time decreased from 4,093 minutes to 3,536 minutes (Reduction of 23.71%). In conclusion, the Tabu Search algorithm significantly enhanced the efficiency of cold chain transportation by reducing fleet size, travel time and total distance traveled. This approach can be practically applied to improve vehicle utilization, minimize product losses and strengthen the competitive and sustainable development of the Thai cold chain industry.
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References
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