Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Resource allocation problems: algorithmic approaches
Resource allocation problems: algorithmic approaches
Managing Large Scale Computational Markets
HICSS '98 Proceedings of the Thirty-First Annual Hawaii International Conference on System Sciences-Volume 7 - Volume 7
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Resource Allocation with Wobbly Functions
Computational Optimization and Applications
IEEE Intelligent Systems
Efficient Resource Allocation with Noisy Functions
WAE '01 Proceedings of the 5th International Workshop on Algorithm Engineering
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We consider resource allocation with separable objective functions defined over subranges of the integers. While it is well known that (the maximization version of) this problem can be solved efficiently if the objective functions are concave, the general problem of resource allocation with non-concave functions is difficult. In this article we show that for fairly well-shaped non-concave objective functions, the optimal solution can be computed efficiently. Our main enabling ingredient is an algorithm for aggregating two objective functions, where the cost depends on the complexity of the two involved functions. As a measure of complexity of a function, we use the number of subintervals that are convex or concave.