The ATA algorithm provides a novel approximation framework for analytic functions that cannot be expressed in closed-form via elementary or algebraic functions. It introduces a hybrid approximation ...

Algorithm Analysis: In-depth discussion of the implemented algorithms, including time and space complexity analysis. Comparative Study: A comparison between the exact and approximation methods in ...

Accurate and efficient solving algorithm is very necessary. Successive Convex Approximation Conversion to NLP Problem Linear Approximation In section Optimal Operation Model for ER-Based AC/DC HDN, ...

A new outer approximation algorithm is proposed for solving general convex programs. A remarkable advantage of the algorithm over existing outer approximation methods is that the approximation of the ...

Scheduling task graphs with communication delay is a widely studied NP-hard problem. Many heuristics have been proposed, but there is no constant approximation algorithm for this classic model. In ...

The expectation-maximization (EM) algorithm is a powerful computational technique for locating maxima of functions. It is widely used in statistics for maximum likelihood or maximum a posteriori ...

In scheduling theory, the non-preemptive scheduling on a single machine of jobs with increasing processing times and release dates for total completion time minimization is known to be a strongly ...

The long-reigning champ of approximation One of the first and most famous approximation algorithms is for the traveling salesperson problem and is known as the Christofides-Serdyukov algorithm.