Controlled jump process models for stochastic scheduling problems
- 1 June 1979
- journal article
- research article
- Published by Taylor & Francis in International Journal of Control
- Vol. 29 (6) , 1011-1025
- https://doi.org/10.1080/00207177908922746
Abstract
A series of controlled jump process models is presented for stochastic scheduling problems. In each case, the optimality principle of dynamic programming is used to reduce the problem to a deterministic optimal control problem. Applying the maximum principle to this deterministic problem yields necessary optimality conditions. These enable explicit optimal scheduling strategies to be found for a number of problems.Keywords
This publication has 4 references indexed in Scilit:
- A hamiltonian approach to optimal stochastic resource allocationAdvances in Applied Probability, 1977
- A Minimum Principle for Controlled Jump ProcessesPublished by Springer Nature ,1975
- Feedback control of a class of linear systems with jump parametersIEEE Transactions on Automatic Control, 1969
- A Renewal Problem with Bulk Ordering of ComponentsJournal of the Royal Statistical Society Series B: Statistical Methodology, 1959