Error bounds for cone inclusion problems in Banach spaces are established under conditions weaker than Robinson’s constraint qualification. The results allow the cone to be more general than the origin and therefore also generalize a classical error bound result concerning equality-constrained sets in optimization. Applications in finite-dimensional differentiable inequalities and in tangent co...

This paper presents the multiclass classifier based on analytical center of feasible space (MACM). This multiclass classifier is formulated as quadratic constrained linear optimization and does not need repeatedly constructing classifiers to separate a single class from all the others. Its generalization error upper bound is proved theoretically. The experiments on benchmark datasets validate t...

In this paper we formulate three classes of optimization problems: the simple, monotonically-constrained, and bounded CH-programs. We reveal the dominance property under the local reenement (LR) operation for the simple CH-program, as well as the general dominance property under the pseudo-LR operation for the monotonically-constrained CH-program and the extended-LR operation for the bounded CH...

nowadays, different methods are used to solve optimization problems which ,one of the newest is bco method that are inspired by the nature and derived from the social life of bees of these methods can be noted that bco is derived from the social life of bees. we use in this paper fuzzy logic for bee‟s decision stage. at the end, we solve two different problem that have already been solved by es...

In this paper we formulate three classes of optimization problems: the simple, monotonically constrained, and bounded Cong–He (CH)-programs. We reveal the dominance property under the local refinement (LR) operation for the simple CH-program, as well as the general dominance property under the pseudo-LR operation for the monotonically constrained CH-program and the extended-LR operation for the...

| In this paper we formulate three classes of optimization problems: the simple, monotonically-constrained, and bounded CH-programs. We reveal the dominance property under the local reenement (LR) operation for the simple CH-program, as well as the general dominance property under the pseudo-LR operation for the monotonically-constrained CH-program and the extended-LR operation for the bounded ...

General Optimization Methods Mathematical Programming, Constraint Programming, Heuristics Problem Specific Algorithms (Dynamic Programming, Branch and Bound) Scheduling Single and Parallel Machine Models Flow Shops and Flexible Flow Shops Job Shops Resource-Constrained Project Scheduling Timetabling Interval Scheduling, Reservations Educational Timetabling Workforce and Employee Timetabling Tra...

This paper describes libcgrpp, a GNU-style dynamic shared Python/C library of the continuous greedy randomized adaptive search procedure (C-GRASP) for bound constrained global optimization. C-GRASP is an extension of the GRASP metaheuristic (Feo and Resende, 1989). After a brief introduction to C-GRASP, we show how to download, install, configure, and use the library through an illustrative exa...

In this paper we consider a PDE-constrained optimization problem where an H1 regularization control term is introduced. We address both timeindependent and time-dependent versions. We introduce bound constraints on the state, and show how these can be handled by a Moreau-Yosida penalty function. We propose Krylov solvers and preconditioners for the different problems and illustrate their perfor...

This study presents a new two-swarm cooperative sh intelligence algorithm for solving the bound constrained global optimization problem. The master population is moved by a Lévy distribution and cooperates with the training population that follows mainly the classical sh behaviors. Some numerical experiments are reported.