Abstract

Optimising the cost of operations is one of the major issues in any urban road transport organisations (URTOs). In this study, a decision problem on location of depots (adding new locations and removing existing ones) and allocation of buses to depots is considered, as observed in one of the major URTOs in India. The main focus of this research is to provide analytic methods to minimise the cost of operations comprising: 1) dead-kilometre cost; 2) fixed cost associated with introducing new depots; 3) salvage value due to closing the depots. To do so, a (0-1) mixed integer linear programming (MILP) model is proposed and its workability is demonstrated. In addition, a simple greedy heuristic algorithm is also proposed. A computational experiment is developed to understand the performance efficiency of the proposed greedy heuristic algorithm in comparison with the optimal solution. From the average and worst case analyses of the performance evaluation, it is observed that the proposed greedy heuristic algorithm provides near-optimal solution. The (0-1) MILP model and the efficient greedy heuristic algorithm proposed in this study can be used to help make better decisions on location of depots and allocation of buses to depots of URTOs in general.

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