Multi-period heterogeneous vehicle routing considering carbon emission trading

This study considers the problem of determining heterogeneous vehicle routes in each period of a given planning horizon while satisfying service combinations, customer demands and vehicle capacities. The objective is to minimize the sum of vehicle operation costs and carbon emission trading cost/benefit, where the trading cost is incurred to purchase the carbon emission right if the total emission exceeds an upper limit in each period, while the trading benefit can be obtained by selling the right in each period, otherwise. A mixed integer programming model is developed to formulate the problem mathematically. Then, a tabu search algorithm is proposed that incorporates the characteristics of the heterogeneous and the period vehicle routing problems while considering the amount of carbon emission in each period. Computational experiments were done on modified benchmark instances and additional random instances, and the results show that the multi-period approach outperforms the existing single-period one in overall average. In particular, the test results show that the multi-period approach can reduce carbon emission more significantly than the single-period one without sacrificing the total cost.