Generating an Efficient Way of Dispatching Perishable Product Optimization through Exact and Metaheuristic Algorithm Comparison

Conveying product which has a limited shelf-life optimally is the concern of this study. The primary attribute of this product is perishable within a specific time frame. However, the perishable product has a critical issue in the cold chain system which leads dispatching costs inefficiency problems. Regarding this problem, a mathematical model built thru extended a vehicle routing problem, with soft time windows (VRPSTW) by considering energy consumption cost to evaluate its contribution towards the objective function. Model building conducted into computer programming that uses Python Spyder 3 for generating a feasible solution. For the sake of feasibility, a metaheuristic approach of genetic algorithms provided to find the best optimal solution; the results diagnosed that genetic algorithms can generate best feasible solution efficiently within a certain number of variables in case of perishable product delivery.

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