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 ...

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, ...

The Traveling Salesman Problem (TSP) is a well-known problem in optimization, where the objective is to find the shortest route to visit all cities and return to the starting point. This project ...

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.