Single-machine batch delivery scheduling with an assignable common due date and controllable processing times

• Published in: Computers & industrial engineering Vol. 65; no. 4; pp. 652 - 662
• Main Authors: Yin, Yunqiang, Cheng, T.C.E., Cheng, Shuenn-Ren, Wu, Chin-Chia
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.08.2013; Pergamon Press Inc
• Subjects: Algorithms; Assignment problem; Batch delivery; Common due date; Deliveries; Dynamic programming; Job shops; Optimization algorithms; Production scheduling; Resource allocation; Scheduling; Studies; Transportation problem (Operations research); Scheduling; Common due date; Batch delivery; Resource allocation
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2013.05.003

•We consider single-machine batch delivery scheduling with an assignable common due date and controllable processing times.•We first provide an O(n5) dynamic programming algorithm to find the optimal job sequence.•We show that a special case of the problem with a lower-order polynomial time and develop an O(nlogn) algorithm to solve it. We consider single-machine batch delivery scheduling with an assignable common due date and controllable processing times, which vary as a convex function of the amounts of a continuously divisible common resource allocated to individual jobs. Finished jobs are delivered in batches and there is no capacity limit on each delivery batch. We first provide an O(n5) dynamic programming algorithm to find the optimal job sequence, the partition of the job sequence into batches, the assigned common due date, and the resource allocation that minimize a cost function based on earliness, tardiness, job holding, due date assignment, batch delivery, and resource consumption. We show that a special case of the problem can be solved by a lower-order polynomial algorithm. We then study the problem of finding the optimal solution to minimize the total cost of earliness, tardiness, job holding, and due date assignment, subject to limited resource availability, and develop an O(nlogn) algorithm to solve it.