Low-carbon vehicle scheduling problem and algorithm with minimum-comprehensive-cost

To solve the problems that the economic benefits of enterprises was ignored by the present low-carbon vehicle scheduling model and the entire cost of vehicle scheduling could not be reflect, on the basis of fuel cost-carbon emission cost-fixed cost model, the Minimum-Comprehensive-Cost vehicle Scheduling Model (MCCVSM) distinguished from minimum-carbon-emission model was established by introducing vehicle depreciation cost, drivers' wage cost and tire-consumption cost. To solve MCCVSM, a new hybrid genetic algorithm was proposed which got the initial population through Sweep algorithm and random permutation operator, and design the elitist operator with tabu search algorithm. The traditional crossover operator was improve with this algorithm. A comparing experiment among the minimum-carbon-emission model, fuel cost-carbon emission cost-vehicle depreciation cost model and minimum-comprehensive-cost model was made to test the rationality of the proposed model. Further, the effectiveness of the proposed hybrid genetic algorithm was proved by standard cases simulation test. ©, 2015, CIMS. All right reserved.