Due-date setting and priority sequencing in a multiclass M/G.1 queue
Management Science
Applied combinatorics (3rd ed.)
Applied combinatorics (3rd ed.)
Single facility due date setting with multiple customer classes
Management Science
Management Science
Selecting jobs for a heavily loaded shop with lateness penalties
Computers and Operations Research
Job selection in a heavily loaded shop
Computers and Operations Research
Submodular Returns and Greedy Heuristics for Queueing Scheduling Problems
Operations Research
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Order acceptance with weighted tardiness
Computers and Operations Research
Order acceptance using genetic algorithms
Computers and Operations Research
Computers and Operations Research
The capacity planning problem in make-to-order enterprises
Mathematical and Computer Modelling: An International Journal
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We examine the profitability of job selection decisions over a number of periods when current orders exceed capacity with the objective of maximizing profit (per-job revenue net of processing costs, minus weighted lateness costs), and when rejecting a job will result in no future jobs from that customer. First we present an optimal dynamic programming algorithm, taking advantage of the structure of the problem to reduce the computational burden. Next we develop a number of myopic heuristics and run computational tests using the DP as benchmark for small problems and the best heuristic as benchmark for larger problems. We find one heuristic that produces near-optimal results for small problems, is tractable for larger problems, and requires the same information as the dynamic program (current and future orders), and another that produces good results using historical information. Our results have implications for when it is more or less worthwhile to expend resources to maintain past records and obtain future information about orders.