Scheduling tasks with due dates in a fabrication/assembly process
Operations Research
A new approach to the maximum-flow problem
Journal of the ACM (JACM)
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special issue on low-power design
Polynomial Methods for Separable Convex Optimization in Unimodular Linear Spaces with Applications
SIAM Journal on Computing
Beyond the flow decomposition barrier
Journal of the ACM (JACM)
Solving the Convex Cost Integer Dual Network Flow Problem
Proceedings of the 7th International IPCO Conference on Integer Programming and Combinatorial Optimization
Resource-Constrained Project Scheduling: Computing Lower Bounds by Solving Minimum Cut Problems
ESA '99 Proceedings of the 7th Annual European Symposium on Algorithms
The project scheduling problem with irregular starting time costs
Operations Research Letters
Solving Project Scheduling Problems by Minimum Cut Computations
Management Science
Computers and Operations Research
Scheduling an r&d project with quality-dependent time slots
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
An efficient hybrid search algorithm for various optimization problems
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
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Maniezzo and Mingozzi (Oper. Res. Lett. 25 (1999) 175-182) study a project scheduling problem with irregular starting time costs. Starting from the assumption that its computational complexity status is open, they develop a branch-and-bound procedure and they identify special cases that are solvable in polynomial time. In this note, we present a collection of previously established results which show that the general problem is solvable in polynomial time. This collection may serve as a useful guide to the literature, since this polynomial-time solvability has been rediscovered in different contexts or using different methods. In addition, we briefly review some related results for specializations and generalizations of the problem.