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  • "Муравьиный алгоритм" как способ повышения эффективности доставки на "последней миле" в розничной интернет-торговле

Article

"Муравьиный алгоритм" как способ повышения эффективности доставки на "последней миле" в розничной интернет-торговле

Виноградов А. Б., Юнеева Д. Р.

Growth rates of internet retailing in Russia outperform brick-and-mortar segment, raising attractiveness of e-commerce for the new players. However growing number of newcomers make e-tailers seek new competitive advantages and pay specific attention to the logistics support of their businesses. Last mile delivery tends to be one of the most important, though also problematic logistics processes in the online retailing.  Potential area of improvement for this process involves application of the heuristic routing methods.  These methods allow to find close to optimal solution spending much less resources compared to the traditional methods.

The paper focuses on the heuristic method of the travelling salesman problem solution, complicated by the specifics of internet retailing (big number of clients and, hence, the delivery points). This method is based on the simulation of the behaviour of ants seeking the shortest path between their colony and the source of food. The authors describe the mathematical model of the ant colony optimization algorithm (ACO) and review its basic steps using the numerical example. Steps of the ACO include definition of the number of nodes, distance between them as well as pheromone concentration; location of couriers (delivery vans) in the nodes; identification of the probability of moving from the initial point (node) to all other points; selection of the movement direction; repetition of the preceding steps (apart from the initial one) for the new node and for the following ones up to the end of the cycle; pheromone renewal; accomplishment of the next cycles (iterations); finding of the shortest delivery route. Comparative analysis has shown major ACO benefits including fast solution of high-dimensional problems and algorithm applicability for the non-stationary systems with the changing parameters (much resembling an online retailing). An opportunity to apply ACO for the last mile delivery routing referring to the vast majority of e-tailers will significantly depend on the speed of development and proliferation of the respective software as well as on improving of selection and adaptation of the algorithm fine-tuning parameters.