چكيده به لاتين
Maintaining security plays a significant role and has a vital necessity and an important priority in transporting certain types of goods. Nowaday, is paid special attention to considering high security in cash transmision Because of important role of cash in people life. 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 order to reduce the risk, it is necessary to anticipate and prevent the occurrence of a terrorist attack. In this thesis, 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 windows is developed where the risk of transfers (including armed terrorist attack and theft) and the distance travelled by vehicles are minimized. The objective of minimizing the risk depends on the amount of cash transported, the probability of a robbery's armed attack and the probability of theft. The probability of robber's ambush is estimated by the game theory approach, in such a way that a two-player, zero-sum game is played between the terrorist and the cash carrier. The Nash equilibrium of game is a combination strategy of a set of player strategies. 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 other words, in order to unpredictable cash transportation routes for the armed robber, 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.
