A new game theoretical multi objective evolutionary approach for cash in transit vehicle routing problem with time windows (A Real life Case)
Abstract Cash transfer from a central treasury to bank branches, which is with high security, is one of the crucial processes in the banking system. In this paper, a new multi objective game theory based model is developed to increase the security of cash in transit. For this purpose and in order to reduce the transportation costs, a bi objective vehicle routing problem with time window is developed where the risk of transfers (including armed robbers attack and theft) and the distance traveled by vehicles are minimized. In order to better estimate the robber's performance, the probability of robber's ambush is calculated by the game theory approach, in such a way that a two player, zero sum game is played between the robber and the cash carrier. The probability of theft success is also estimated in the proposed approach through a multiple criteria decision making and in order to be further representative of real life situations. A periodic review is also added to the proposed model to increase the cash transport security in which the previously used links would enjoy less chance of choosing in the current period. Moreover, a new multi objective hybrid genetic algorithm incorporated with a number of new heuristics and operators is developed to tackle the proposed model. The efficiency and effectiveness of the algorithm are examined through several standard data sets, and the results indicate the effectiveness of the proposed solution algorithm. The wide applicability of our proposed approach in real life situations is examined with a real case study as well.
Appl. Soft Comput.