Multi-objective and blockchain based optimization algorithm for fleet sharing management

With the rise in the demand for the fleet in today's time even for covering a small distance, taxis play a crucial role not only in terms of ease in traveling but also in generating profit economically. Every advantage comes up with the side effects behind it such as the increase in profit along with the comfort of the customers have effects on the environment and also have issues related to the trust. Use of these services in excess sometimes poses a major threat to the environment in terms of doubling the traffic volume as the personal vehicles along with the hired vehicle volume are added together. It will also increase pollution which will affect our health. So, there is a need to devise a way that minimizes the negative effects of these services along with the increase in economic performance. This paper deals with the sharing ability of these platforms so that optimal allocation of passengers will be done to minimize the side effects and also to increase the overall usage of the fleet. However, the sharing ability of these services comes up with the disadvantage of having a trust issue among the users. So, to deal with this problem, we incorporate the blockchain concept here. This study includes the multi-objective functions such as the shortest route, maximal allocation of the passenger along with the minimization of cost which in turn reduces its effect on the environment, and minimization of trust-related problems with respect to the constraints such as demand, time, and supply. This study proposes two different optimization algorithms to solve this problem. The first one is based on considering one objective in each stage at a time where the objectives are dependent on each other whereas the second one is the formulation of a Multi-objective optimization algorithm by taking all the objectives from all the stages together with their respective weights by keeping in mind the problems related to these services. A case study is done based on this problem and solved using the computational approach with the first algorithm with the help of programming languages.