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J. B. G. Frenk

Bio: J. B. G. Frenk is an academic researcher from Sabancı University. The author has contributed to research in topics: Minimax & Convex analysis. The author has an hindex of 23, co-authored 105 publications receiving 1634 citations. Previous affiliations of J. B. G. Frenk include Econometric Institute & University of California, Berkeley.


Papers
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Journal ArticleDOI
TL;DR: Several examples of one‐machine problems in which the minimization of expected cost subject to stochastic breakdowns of the machine can be successfully attacked analytically are provided.
Abstract: We provide several examples of one-machine problems in which the minimization of expected cost subject to stochastic breakdowns of the machine can be successfully attacked analytically. In particular for the weighted flow-time model, we derive strong bounds on the difference between the optimal static policy and the WSPT policy and discuss an example in which the WSPT policy is not optimal.

104 citations

Journal ArticleDOI
TL;DR: In this article, an alternative optimal approach based on global optimisation theory is presented, which uses a dynamic Lipschitz constant and generates a solution in little time, and the running time of this procedure grows only linearly in the number of items.

81 citations

Journal ArticleDOI
TL;DR: A new dual problem for convex generalized fractional programs with no duality gap is presented and it is shown how this dual problem can be efficiently solved using a parametric approach using the Dinkelbach-type algorithm.
Abstract: A new dual problem for convex generalized fractional programs with no duality gap is presented and it is shown how this dual problem can be efficiently solved using a parametric approach. The resulting algorithm can be seen as “dual” to the Dinkelbach-type algorithm for generalized fractional programs since it approximates the optimal objective value of the dual (primal) problem from below. Convergence results for this algorithm are derived and an easy condition to achieve superlinear convergence is also established. Moreover, under some additional assumptions the algorithm also recovers at the same time an optimal solution of the primal problem. We also consider a variant of this new algorithm, based on scaling the “dual” parametric function. The numerical results, in case of quadratic-linear ratios and linear constraints, show that the performance of the new algorithm and its scaled version is superior to that of the Dinkelbach-type algorithms. From the computational results it also appears that contrary to the primal approach, the “dual” approach is less influenced by scaling.

78 citations

Journal Article
TL;DR: This work studies a greedy-type heuristic and refined it to obtain a new heuristic with a worst-case bound of 3/2 that is applicable to the 0-1 min-knapsack problem.
Abstract: textThe 0-1 min-knapsack problem consists in finding a subset of items such that the sum of their sizes is larger than or equal to a given constant and the sum of their costs is minimized. We first study a greedy-type heuristic having a worst-case bound of 2. This heuristic is then refined to obtain a new one with a worst-case bound of 3/2.

68 citations

Journal ArticleDOI
TL;DR: In this paper, the authors considered the problem of finding the set of actions that minimizes the expected (discounted) maintenance costs over both a finite horizon and an infinite horizon, and showed that the optimal maintenance decisions related to this problem are a solution of a continuous-time renewal-type dynamic programming equation.

56 citations


Cited by
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Journal ArticleDOI
TL;DR: This paper systematically reviews the recent modeling developments for estimating the RUL and focuses on statistical data driven approaches which rely only on available past observed data and statistical models.

1,667 citations

Journal ArticleDOI
Hongzhou Wang1
TL;DR: This survey summarizes, classifies, and compares various existing maintenance policies for both single-unit and multi-unit systems, with emphasis on single- unit systems.

1,507 citations

01 Jan 1989
TL;DR: This survey focuses on the area of deterministic machine scheduling, and reviews complexity results and optimization and approximation algorithms for problems involving a single machine, parallel machines, open shops, flow shops and job shops.

1,401 citations