We propose a novel idea of regression – balancing the distances from a regression function to all examples. We created a method, called balanced support vector regression (balanced SVR) in which we incorporated this idea to support vector regression (SVR) by adding an equality constraint to the SVR optimization problem. We implemented our method for two versions of SVR: ε-insensitive support ve...

In this paper, a hybrid method for solving multi-objective problem has been provided. The proposed method is combining the ε-Constraint and the Cuckoo algorithm. First the multi objective problem transfers into a single-objective problem using ε-Constraint, then the Cuckoo optimization algorithm will optimize the problem in each task. At last the optimized Pareto frontier will be drawn. The adv...

this study investigated the efficiency of wheat farms in sistan province. the data consisted of 50 samples from crop producers in the sistan region. using the simple sampling method, the data was collected by completing the questionnaires. to evaluate the farm efficiencies, the two approaches of the “data envelopment analysis” and the “optimization model including parameters to control for the ...

We give a proximal bundle method for minimizing a convex function f over R+. It requires evaluating f and its subgradients with a possibly unknown accuracy ε ≥ 0, and maintains a set of free variables I to simplify its prox subproblems. The method asymptotically finds points that are ε-optimal. In Lagrangian relaxation of convex programs, it allows for ε-accurate solutions of Lagrangian subprob...

This paper considers a bi-objective mathematical model for locations of landfills, transfer stations and material recovery facilities (MRFs) in order to serve the entire regions and simultaneously identify the capacities of landfills. This is a mixed-integer programming (MIP) model, whose objectives are to minimize the total cost and pollution simultaneously. To validate the model, a numerical ...

In general, microgrids have a high renewable energy abandonment rate and grid construction operation costs. To improve the microgrid utilization rate, economic advantages, environmental safety of power operation, we propose hybrid storage capacity optimization method for wind–solar–diesel grid-connected system, based on an augmented ε- constraint method. First, battery is coupled with seasonal ...

A temporal constraint language Γ is a set of relations with first-order definitions in (Q;<). Let CSP(Γ) denote the set of constraint satisfaction problem instances with relations from Γ. CSP(Γ) admits robust approximation if, for any ε ≥ 0, given a (1 − ε)-satisfiable instance of CSP(Γ), we can compute an assignment that satisfies at least a (1−f(ε))-fraction of constraints in polynomial time....

In this paper, a new general scalarization technique for solving multiobjective optimization problems is presented. After studying the properties of this formulation, two problems as special cases of this general formula are considered. It is shown that some well-known methods such as the weighted sum method, the -constraint method, the Benson method, the hybrid method and the elastic -constrai...

An algorithm for a constraint satisfaction problem is called robust if it outputs an assignment satisfying at least (1 − g(ε))-fraction of the constraints given a (1 − ε)-satisfiable instance, where g(ε) → 0 as ε → 0. Guruswami and Zhou conjectured a characterization of constraint languages for which the corresponding constraint satisfaction problem admits an efficient robust algorithm. This pa...