One-processor scheduling with symmetric earliness and tardiness penalties
Mathematics of Operations Research
Sequencing with earliness and tardiness penalties: a review
Operations Research
Minmax earliness/tardiness scheduling in identical parallel machine system using genetic algorithms
ICC&IE '94 Proceedings of the 17th international conference on Computers and industrial engineering
Computers and Industrial Engineering - Special issue: Focussed issue on applied meta-heuristics
Supply chain scheduling: Batching and delivery
Operations Research
Earliness/tardiness scheduling with a common due date and family setups
Computers and Industrial Engineering
A comparison of lower bounds for the single-machine early/tardy problem
Computers and Operations Research
Minimizing total earliness and tardiness on a single machine using a hybrid heuristic
Computers and Operations Research
A branch-and-bound algorithm for single-machine scheduling with batch delivery and job release times
Computers and Operations Research
Computers and Industrial Engineering
Computers and Operations Research
Lot-sizing and scheduling problem with earliness tardiness and setup penalties
Computers and Industrial Engineering
Computers and Industrial Engineering
Minimizing maximum tardiness and delivery costs in a batched delivery system
Computers and Industrial Engineering
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This paper endeavors to solve a novel complex single-machine scheduling problem using two different approaches. One approach exploits mathematical modeling, and the other is based upon genetic algorithms. The problem involves earliness, tardiness, and inventory costs and considers a batched delivery system. The same conditions might apply to some real supply chains, in which delivery of products is conducted in a batched form and with some costs. In such delivery systems, the act of buffering the products can have both positive effects (i.e., decreasing the delivery costs and early jobs) and negative ones (i.e., increasing the number of tardy and holding costs). Accordingly, the proposed solution takes into account both effects and tries to find a trade-off between them to hold the total costs low. The suggestions are compared to existing solutions for older non-batched systems and have illustrated outperformance.