Linear objective function optimization
Optimization over an integer efficient set of a Multiple Objective Linear Fractional Problem
... valued function over an efficient set of the Multiple Objective Linear Programming problem (MOLP) have attracted much attention because of their important applica- tions in decision ...for ...
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A MULTI-OBJECTIVE LINEAR PROGRAMMING MODEL FOR NATIONAL PLANNING
... mathematical optimization problems involving more than one objective function to be optimized ...Multi-objective optimization has been applied in many fields of economics, science, ...
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Design of Time-Modulated Linear Arrays with a Multi-Objective Optimization Approach
... Multi-objective Optimization (MO) framework for the design of time-modulated linear antenna arrays with ultra low maximum Side Lobe Level (SLL), maximum Side Band Level (SBL) and main lobe Beam Width ...
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IMPLEMENTATION OF NON-LINEAR MULTI OBJECTIVE OPTIMIZATION FOR ENERGY MANAGEMENT SYSTEMS.
... optimal objective function ...the objective function of the ...proposed optimization models indicate that the Lagrangian Relaxation technique is capable of solving large problems to the ...
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Linear optimization of fuzzy relation inequalities with max-Lukasiewicz composition
... the linear optimiza- tion problem with fuzzy relational inequalities constraints defined by max-Lukasiewicz ...with objective function c +t x was ...
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Applying Quantum Optimization Algorithms for Linear Programming
... The simplex method is a method for solving problems in linear programming. This method, invented by George Dantzig in 1947, tests adjacent vertices of the feasible set (which is a polytope) in sequence so that at ...
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Solving Multi-Objective Structural Design Problem using Fuzzy Optimization Method: A Comparative Study
... each objective function. We made a comparative study of linear and non-linear membership function to see its impact on optimization and to get to the depth of such ...
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Solving a non-convex non-linear optimization problem constrained by fuzzy relational equations and Sugeno-Weber family of t-norms
... an optimization problem is iteratively evolved toward better solutions (the population in each iteration called a ...the objective function in the optimization problem being ...
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Linear programming on SS-fuzzy inequality constrained problems
... The optimization problem subjected to various versions of FRI could be found in the literature as well [19, 15, 16, 21, 22, 25, 54, ...of linear objective function subject to FRI with ...
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Load Optimization in Mobile Network using Traffic Engineering
... a linear optimization (objective function (4), Figure 1) with the value equal to one channel and minimizing network latency (the objective function (5), Figure 2 ...For ...
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LP problems constrained with D-FRIs
... The remainder of the paper is organized as follows. In section 2, some preliminary no- tions and definitions and three necessary conditions for the feasibility of problem (1) are presented. In section 3, the feasible ...
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A model for development of optimised feeder routes and coordinated schedules: a genetic algorithms approach
... Many attempts have been made to solve bus route network design problems by splitting it in two stages, one for routing and the other for scheduling. Some researchers have made attempts to solve network design problems ...
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Design of feeder route network using combined genetic algorithm and specialised repair heuristic
... penalised objective function (summation of objective function and penalties due to violation of constraints) is developed in ‘C++’ ...which objective function along with ...
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Optimal Design of Structures by the Combined use of Mathematical Models of Corrosion Destruction
... In Fig. 6 shows that the decrease of the depth of total corrosion in the process of evolution of construction till an optimal state is due to the reduction of corrosion, determined by the level of the influence of SSS. ...
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An Introduction to Dynamic Optical Optimization
... offer optimization analysis for such an optical system by defining the focal length of the lens/ mirror as the objective function, while the object distance and lateral magnification ...
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Optimal High Purity Acetone Production in a Batch Extractive Distillation Column
... dynamic optimization technique has been applied by successive quadratic programming (SQP) solving [9], [10], and ...The objective function of the optimization problem is to maximize the weight ...
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A New Filled Function with One Parameter to Solve Global Optimization
... filled function method are given in Section ...filled function is proposed and its properties are ...proximate function of the proposed filled function is ...filled function method is ...
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A Quasi-Newton Population Migration Algorithm for Solving Systems of Nonlinear Equations
... of function, but this paper you can quickly find of a solution via iteration 50 times, success rate is 100%, although PMA algorithm have ability to search equations approximate solutions, Success rate is worse ...
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Duality in Solving Multi Objective Optimization (MOO) Problems
... Multi-Objective Optimization (MOO) techniques often achieve the combina- tion of both maximization and minimization ...four objective functions has been solved using duality with satisfactory ...
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A STATCOM Model for Optimal Power Flows Using Genetic Algorithm
... system optimization problem having objective of minimization of objective function subjected to power balance equality constraints and control, dependent variables limits of inequality ...
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