[PDF] Top 20 An interactive algorithm for solving multiobjective optimization problems based on a general scalarization technique
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An interactive algorithm for solving multiobjective optimization problems based on a general scalarization technique
... available interactive methods brings the need for cre- ating general interactive algorithms enabling the decision maker (DM) to apply freely several convenient methods which best fit his/her ...a ... See full document
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Efficient Multiobjective Genetic Algorithm for Solving Transportation, Assignment, and Transshipment Problems
... search algorithm in order to reach a quick and closer result to the optimum ...recent optimization problems ...search technique is based on a dy- namic version of pattern search ... See full document
8
Multiobjective Service Restoration Considering Primary Customers using Hybrid GA ACO Algorithm
... a general purpose search technique for various optimization ...the optimization problem Genetic algorithm starts with a set of randomly selected chromosomes as the initial population ... See full document
10
LP problems constrained with D-FRIs
... paper, optimization of a linear objective func- tion with fuzzy relational inequality constraints is in- vestigated where the feasible region is formed as the in- tersection of two inequality fuzzy systems and ... See full document
21
Well posed symmetric vector quasi equilibrium problems
... inequality problems [, ], and vector equilibrium problems [–, ...timization problems, vector variational inequality problems, and vector equilibrium prob- lems, the nonlinear ... See full document
10
Optimum Design of a Hybrid PV/Wind Energy System Using Genetic Algorithm (GA)
... an optimization technique to design the hybrid PV/wind ...Genetic Algorithm (GA) optimization technique is utilized to minimize the formulated objective function, ...the ... See full document
11
Solving Bilevel Linear Multiobjective Programming Problems
... decisions. Based on this result and depending if the leader can evaluate or not his preferences for his differ- ent objective functions, two approaches for obtaining Pareto-optimal solutions are ... See full document
6
Tchebycheff Method-based Evolutionary Algorithm for Multiobjective Optimization
... Genetic Algorithm (NSGA- II) [12], Strength Pareto Evolutionary Algorithm (SPEA-II) [27], Multiobjective Genetic Algorithm (MOGA) [15], Niched Pareto Genetic Algorithm (NPGA) ...Pareto ... See full document
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Meta Heuristics approach for a Class of supply chain optimization problems D.Sabareswari, N.Sathya, K.Sharmila Abstract PDF IJIRMET160207006
... combinatorial optimization are characterized by their well-structured problem definition as well as by their huge number of action alternatives in practical application areas of reasonable ...of problems ... See full document
7
Based on Particle Swarm Optimization Algorithm for Finding Ideal and Effective Solution of Dynamic Batch Reactor Multi objective Optimization
... PSO algorithm is a solution in the solution space, which adjusts its flight according to its own flight experience and companion's flight ...the optimization problem in ... See full document
12
A Hybrid Parallel Multi Objective Genetic Algorithm: HybJacIsCone Model
... above technique by considering the guided dominance principle ...above technique gave rise excellent result in the aspect of concurrency to the true Pareto front without guidance ... See full document
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Reactive Search Optimization; Application to Multiobjective Optimization Problems
... approach based on a hybrid operation of reactive tabu search is proposed in ...on problems arising in telecommunication networks, internet and wireless in terms of optimal design, management and reliability ... See full document
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Solving a non-convex non-linear optimization problem constrained by fuzzy relational equations and Sugeno-Weber family of t-norms
... genetic algorithm, a population of solutions (called individuals) to an optimization problem is iteratively evolved toward better solutions (the population in each iteration called a ...and based on ... See full document
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A Hybrid Multi-Agent Routing Algorithm Based on Ant Colony Optimization for MANET
... routing algorithm based on routing table, due to continuously updating routing tables, it consumes large portion of network ...reactive algorithm. In this algorithm, when path breaks, it needs ... See full document
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Multi-Area Economic Dispatch Performance Using Swarm Intelligence Technique Considering Voltage Stability
... EP seeks for the optimal solution of an optimization problem by evolving a population of candidate solutions over a number of iterations [19]. The candidates, which is known as the parent will be used to generate ... See full document
7
Linear programming on SS-fuzzy inequality constrained problems
... In this paper, a linear optimization problem is investi- gated whose constraints are defined with fuzzy relational inequality. These constraints are formed as the intersec- tion of two inequality fuzzy systems and ... See full document
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An optimization algorithm for solving a class of multiplicative problems
... The paper is described as follows. In Sections 2, first we convert the problem (MP) into an equivalent problem (EP), then a new linearizing method is proposed for generating the linear relaxation of the problem (EP). ... See full document
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Sensitivity analysis for parametric vector optimization problems using differential equations approach
... vector optimization prob- lem (VOP) (see ...vector optimization problem, where the parameters in the objective functions and any- where in the ...the technique of trajectory continuation, [5, 6, 8], ... See full document
8
A Novel Technique for Solving Multiobjective Fuzzy Linear Programming Problems
... MFLP problems in (4) under the same set of constraints, it is difficult to find a solution which satisfies all of those objective ...solution algorithm for the method used in this ... See full document
8
An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems Pages 535-560 Download PDF
... population based algorithms is a research field which simulates different natural phenomena to solve a wide range of ...Teaching-Learning-based optimization (TLBO) is one of the recently proposed ... See full document
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