Vehicle routing with time windows and customer selection for perishable goods مقاله

نویسنده: Rabbani، Masoud ؛ Ramezankhani، Mohammad Javad ؛ Farrokhi-Asl، Hamed ؛ Farshbaf-Geranmayeh، Amir ؛

Supply and Operations Management August 2015, Volume 2 - Number 2 (‎20 صفحه - از 700 تا 719 )

کلیدواژه ها: Genetic Algorithm Simulated annealing Vehicle Routing Problem with Time Windows (VRPTW) Perishable Goods Multi-Objective Programming SA Experiment Constraints Time Taguchi

چکیده:

Delivering perishable products to customers as soon as possible and with the minimum cost has been always a challenge for producers and has been emphasized over recent years as the global market becoming more competitive. In this study a multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several products to be delivered to customers with respect to their demands and with consideration of different soft time windows for each customer, heterogeneous distribution fleet and customer selection option for the distributer. The proposed model is solved with TH method. The two genetic algorithm and simulated annealing algorithm are used to solve large-sized problems. Finally, their results are compared to each other when the optimization software becomes unable of solution representation.

خلاصه ماشینی:

Vehicle routing with time windows and customer selection for perishable goods Masoud Rabbani* a, Mohammad Javad Ramezankhani a, Hamed Farrokhi-Aslb and Amir Farshbaf-Geranmayeh a a School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran b School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran Abstract Delivering perishable products to customers as soon as possible and with the minimum cost has been always a challenge for producers and has been emphasized over recent years as the global market becoming more competitive. In this study a multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several products to be delivered to customers with respect to their demands and with consideration of different soft time windows for each customer, heterogeneous distribution fleet and customer selection option for the distributer. A hybrid combination of genetic algorithms and construction heuristic for vehicle routing was proposed in the problem of scheduling and distributing ready-mixed concrete supply chain which is a perishable product (Naso, Surico, Turchiano, & Kaymak, 2007). A multi-objective mathematical formulation of VRP with hard time windows and homogeneous fleet has been proposed and an evolutionary algorithm is implemented for large-size problems (P Amorim & Almada-Lobo, 2014). Similarly, a bi-objective inventory routing problem for perishable goods by considering customer satisfaction level has been published recently which could be used as an extension for future studies (Rahimi, Baboli, & Rekik, 2014).

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