In this paper, an integer programming model is developed for a newly addressed coke production scheduling problem, in which two typical characteristics are considered: (i) The transportation of raw coal by a vehicle causes a batch preprocessing; (ii) The heating of raw coal by closely located coke ovens may extend the processing times of cokes, under the temperature influence. To the best of our knowledge, such a geographically location-dependent processing time has not been studied. The purpose is to minimize the completion time of the last coke among all ovens, i.e., the makespan. Therefore, the problem of interest can be viewed as a parallel machine makespan minimization scheduling problem, featured with batch preprocessings and location-dependent processing times. For this NP-hard problem, a problem-specific genetic algorithm and a fast heuristic are devised to enhance the computational efficiency. Experimental results on 330 randomly generated instances show the effectiveness and efficiency of the proposed solution methods.