Production and Delivery Batch Scheduling with Multiple Due Dates to Minimize Total Cost

Abstract

Abstract. This paper addresses an integrated production and delivery batch scheduling problem for a make-to-order environment over daily time period, where the holding costs of in-process and completed parts at a supplier location and of completed parts at a manufacturer location are distinguished. All orders of parts with different due dates from the manufacturer arrive at the same time. The parts are produced in production batches and subsequently the completed parts are delivered in delivery batches using a capacitated vehicle in order to be received at the respective due dates. This study was aimed at finding an integrated schedule of production and delivery batches so as to meet the due date at minimum total cost consisting of the corresponding holding cost and delivery cost. The holding cost is a derivation of the so-called actual flow time (AFT), while the delivery cost is assumed to be proportional to the number of deliveries. The problems can be formulated as an integer non-linear programming model, and the global optimal solution can be obtained using optimization software. A heuristic algorithm is proposed to cope with the computational time problem using software. The numerical experiences show that the proposed algorithm yields near global optimal solutions.

Single Machine Slack Due-Window Scheduling With Linear Resource Allocation and Position-Dependent Processing Times

“…We solved the single machine scheduling and slack due-window assignment problems with position-dependent processing times for the linear resource allocation models, and presented a polynomial-time solutions to minimize the total cost caused by the due-window location, due-window size, earliness, tardiness, resource consumption and makespan. Further research may consider the problem with other objective functions, or the problem with other settings, e.g., production and delivery batch scheduling [8], [9] and [10].…”

“…The global optimal solution for this example includes the following: (i) the job sequence is (6, 1, 7, 4, 3, 5, 2) and the corresponding job starting time and actual processing time are (0, 6, 12, 18, 22, 31, 52) and (6,6,6,4,9,21, 30), respectively; (ii) the slack window parameters are q = 18 and q ′ = 31; (iii) the optimal resource consumption of each job is (8, 0, 7, 6, 6, 6, 7); (iv) the total cost is Z = 3203.60.…”