Minimizing resource availability costs in time-limited project networks
Management Science
Resource-constrained project scheduling: a survey of recent developments
Computers and Operations Research
A branch-and-cut algorithm for scheduling of projects with variable-intensity activities
Mathematical Programming: Series A and B
Time-constrained project scheduling with adjacent resources
Computers and Operations Research
Electrical load management in smart homes using evolutionary algorithms
EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization
A mathematical model for the management of a Service Center
Mathematical and Computer Modelling: An International Journal
Production scheduling of assembly fixtures in the aeronautical industry
Computers and Industrial Engineering
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We propose a new approach for scheduling with strict deadlines and apply this approach to the Time-Constrained Project Scheduling Problem (TCPSP). To be able to meet these deadlines, it is possible to work in overtime or hire additional capacity in regular time or overtime. For this problem, we develop a two stage heuristic. The key of the approach lies in the first stage in which we construct partial schedules. In these partial schedules, jobs may be scheduled for a shorter duration than required. The second stage uses an ILP formulation of the problem to turn a partial schedule into a feasible schedule, and to perform a neighborhood search. The developed heuristic is quite flexible and, therefore, suitable for practice. We present experimental results on modified RCPSP benchmark instances. The two stage heuristic solves many instances to optimality, and if we substantially decrease the deadline, the rise in cost is only small.