Titlebook: Optimization and Applications; 9th International Co Yury Evtushenko,Milojica Jaćimović,Mikhail Posypki Conference proceedings 2019 Springer

Defense

Subgradient Method with Polyak’s Step in Transformed Spacea given accuracy by the value of the function was performed. Examples of ravine convex (smooth and non-smooth) functions are given, for which convergence of method A is slow. It is shown that with a suitable choice of the space transformation matrix method B can be significantly accelerated in comparison with method A for ravine convex functions.

inscribe

Mirror Descent and Constrained Online Optimization Problemsecently proposed adaptive methods of Mirror Descent the method is suggested to solve the mentioned constrained online optimization problem with an optimal estimate of accuracy. For the corresponding non-Euclidean prox-structure, the case of a set of .-dimensional vectors lying on the standard .-dimensional simplex is considered.

Tonometry

Primal-Dual Newton’s Method with Steepest Descent for Linear Programming minimization of the dual gap. The safety factor is not introduced, and trajectories are allowed to move along the boundaries of the feasible sets. The convergence of the method at a finite number of iterations is proved.

成绩上升

Improved Polynomial Time Approximation Scheme for Capacitated Vehicle Routing Problem with Time Windere . is the given vehicle capacity bound, . is the number of time windows for servicing the customers, and . is the time needed to find a .-approximate solution for an auxiliary instance of the metric TSP.

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DEFER

Minimization of the Weighted Total Sparsity of Cosmonaut Training Coursesr solving the thoroughly studied RCPSP with the makespan criterion. New heuristic algorithms for solving this problem are proposed. Their efficiency is verified on real-life data. In a reasonable time, the algorithms let us find a solution that is better than the solution found with the help of the solver CPLEX CP Optimizer.

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Mirage

Yury Evtushenko,Milojica Jaćimović,Mikhail Posypki

倔强一点

Grigorii E. Ivanov,Mariana S. Lopushanski,Maxim O. Golubev