Optimization Problems
Solving Constrained Multilocal Optimization Problems with Parallel Stretched Simulated Annealing
... programming optimization problems may be solved by solving a sequence of unconstrained ...unconstrained problems may be solved using techniques like the Stretched Simulated Annealing (SSA) ...
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Differential Evolution Enhanced with Eager Random Search for Solving Real-Parameter Optimization Problems
... real-world optimization problems. They are population-based optimization approaches [1] which perform parallel and beam search, thereby exhibiting strong global search ability in complex and high ...
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Smoothed Lower Order Penalty Function for Constrained Optimization Problems
... Based on the lower order penalty function, this paper introduces a smoothing lower order penalty function method which differs from the smoothing penalty function methods in [12], [13], [15], and proposes a corresponding ...
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AN ADAPTIVE CONSTRAINT HANDLING TECHNIQUE FOR PARTICLE SWARM IN CONSTRAINED OPTIMIZATION PROBLEMS
... constrained optimization problems, which are common in real world ...swarm optimization (PSO) technique to solve constrained optimization ...test- problems and 5 mechanical engineering ...
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SOLVING BIPOLAR MAX-TP EQUATION CONSTRAINED MULTI-OBJECTIVE OPTIMIZATION PROBLEMS
... objective optimization problem (2), we face the challenge of solving the bipolar max- T p equation constrained optimization problems (3), (4), (6) or ...constrained optimization problem are ...
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On some optimization problems in not necessarily locally convex space
... Abstract: In this note, by using O. Hadži ć's generalization of a fixed point theorem of Himmelberg, we prove a non - cooperative equilibrium existence theorem in non - compact settings and a generalization of an ...
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Solving Multilocal Optimization Problems with a Recursive Parallel Search of the Feasible Region
... The search for optima of nonlinear optimization functions through the SSA method is easily parallelizable. SSA searches for solutions in a given feasible region (search domain) by following a stochastic algorithm. ...
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High-performance Scientific Computing using Parallel Computing to Improve Performance Optimization Problems
... electrostatic optimization problem using the Parallel Computing Toolbox that allows solving computational and data-intensive problems using MATLAB and Simulink on multicore and multiprocessor ...
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Central limit theorems for risk averse optimization problems
... for problems of type (1) and (2) when R is an ...for problems of type (1) and (2) when R is a law invariant coherent risk measure, using results established in ...portfolio problems and we perform ...
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A multi-objective Pareto ant colony algorithm for the Multi-Depot Vehicle Routing problem with Backhauls
... In the AS, an artificial colony of ants cooperates to find good solutions for discrete, static, and dynamic combinatorial optimization problems. Three different variants for the AS have been proposed: Ant- ...
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A Modified BFGS Formula Using a Trust Region Model for Nonsmooth Convex Minimizations.
... nonlinear optimization, and it has been proven to be a very efficient ...least-squares problems, and Powell [21] established a conver- gence result for this method for unconstrained ...nonsmooth ...
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Particle Swarm Optimization Approach For Economic Load Dispatch: A Review
... dispatch problems. BFT was already used for optimization problems, and performance of basic BFT for small problems with moderate dimension and searching space was ...ELD problems, and ...
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Comput. Appl. Math. vol.31 número3
... two optimization types that explicitly incorporate data whose values are not real-valued nor probabilistic: 1) flexible optimization and 2) optimization under generalized ...Flexible ...
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Pesqui. Oper. vol.23 número1
... combinatorial optimization problems using commercial codes of mixed linear integer programming as CPLEX, LINDO, OSL, XPRESS, ...these problems needs a hard work of ...combinatorial ...
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Pesqui. Oper. vol.35 número3
... three problems and the four metaheuristics used in the ...discrete optimization problems has the double advantage of working with algorithms based on models already known and the effi- ciency of the ...
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Comput. Appl. Math. vol.25 número1
... optimization problems. In general, the algorithms used to solve optimization problems obtain stationary points, that is, points that only satisfy the first order optimality ...
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On the treewidths of graphs of bounded degree.
... Tree decomposition is one of the most important concepts developed in graph theory in the past two decades. In a tree decomposition, graph vertices are grouped into vertex subsets, each of the vertex subsets is ...
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On the Eigenvalues Distribution of Preconditioned Block Two-by-two Matrix
... Abstract—The spectral properties of a class of block 2 × 2 matrix are studied, which arise in the numercial solutions of PDE-constrained optimization problems. Based on the Schur complement approximate ...
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A Constrained Genetic Algorithm Based on Constraint Handling with KS Function and Grouping Penalty
... Because of each constraint handling methods may Only suitable for a certain class of optimization problems. This paper presents a method KS-GPGA merging KS aggregate constraint function and grouping penalty ...
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A Hybrid Genetic Algorithm for Constrained Combinatorial Problems: An Application to Promotion Planning Problems
... The weekly problem faced by SIC, typically involves the broadcast of about 1350 spots, chosen from around 90 different ones, in roughly 200 time slots. The dura- tion of each of these time slots, here and hereafter ...
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