In previous work, under some assumptions, we specified a replacement rule which minimizes the long-run (expected) average cost per unit time and possesses control limit property. In this paper, a general algorithm for such models is developed....
One of them is the Hungarian algorithm of Kuhn [85] or its variant of Munkres [96] that has a worst-case computational complexity of at most O(n 4). Another alternative is the class of net flow algorithms described in [89, Chapter 6]. In particular, the algorithm of Edmonds and Karp...
Multistate System Reliability Analysis and Optimization (Universal Generating Function and Genetic Algorithm Approach) On the importance of different components in a multicomponent system. In: Krishnaiah PR, editor. Multivariate analysis 2. New York: Academic Press; 1969. Barlow RE, Proschan F. Import...
摘要: Page 1. Near-Optimal Hashing Algorithms for Approximate Near(est) Neighbor Problem 24 is42 in reverse… Very fast (bounded) decoder: about 519 operations [Amrani-Beery'94] or cameup with a really neat lattice… – Tight lower bound Non-immediate questions...
5 In Appendix A, we provide an algorithm for solving this class of models with both forward-looking constraints and imperfect public monitoring.6 Our results on the consequences of imperfect credibility for optimal policy design differ from those of the “loose commitment” approach originally ...
Section 3.3 describes the algorithm used to solve the SBO. 3.1. Multi-criteria optimization model The decision variables of the multi-criteria optimization model are the prices for the rate components, denoted by the vector p. This study targets the rate design principles of economic efficiency, ...
``A Branch-and-Bound Algorithm for Computing Optimal Replace- ment Policies in K-Out-Of-N Systems.55 Operations Research 43, 826-837.Flynn, J, Chung, C.S.: A branch and bound algorithm for computing optimal replacement policies in consecutive k-out-of-n systems. Naval Research Logistics ...
This paper innovates, within the context of preventive maintenance planning, the application of Genetic Algorithm, as a modern powerful optimization tool, in minimum downtime strategies, for optimal part replacement. Therefore, a brief account of Genetic Algorithm is given and a computer program is ...
Before executing this new instance, the scheme may also adjust the algorithm’s parameters. Under the right conditions, the objective function error and the feasibility gap decay faster with the restarted scheme than with the standard (non-restarted) first-order method. In this work, we relax ...
We show that the discrete Sinkhorn algorithm—as applied in the setting of Optimal Transport on a compact manifold—converges to the solution of