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Goal Programming Based Multi-Objective Optimization Techniques of Task Allocation in Distributed Environment

task allocation problem as a multi-objective optimization problem to consider system constraints. The goal programming technique is used with;

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Advanced Optimization and Decision-Making Techniques in Textile Manufacturing

demonstrate the confluence of theory and applications of various types of multi-criteria decision making and optimization techniques with reference to;

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Advanced Optimization and Decision-Making Techniques in Textile Manufacturing

demonstrate the confluence of theory and applications of various types of multi-criteria decision making and optimization techniques with reference to;

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Fundamentals of Optimization Techniques with Algorithms

linear and nonlinear single variable and multivariable models, as well as multi-objective and advanced optimization techniques. It presents both;

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Portfolio Selection Using Multi Objective Optimisation

-objective optimization. Next to outlining techniques for undertaking individual investor's profiling and portfolio programming, it also offers a new;

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Optimization Techniques in Operation Research

new chapters - Introduction to Optimization and Classical Optimization Techniques , more solved and unsolved examples, and a new article on;

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Evolutionary Constrained Optimization

evolutionary algorithms. Broadly the topics covered include constraint handling for single and multi-objective optimizations; penalty function based;

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Distributed Heterogeneous Multi Sensor Task Allocation Systems

multi-sensor allocation. This book presents the theory and applications of novel methods developed for such sophisticated systems. It discusses;

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Distributed Heterogeneous Multi Sensor Task Allocation Systems

multi-sensor allocation. This book presents the theory and applications of novel methods developed for such sophisticated systems. It discusses;

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Distributed Optimization-Based Control of Multi-Agent Networks in Complex Environments

This book offers a concise and in-depth exposition of specific algorithmic solutions for distributed optimization based control of multi;

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Engineering Optimization

of convex functions, and goal programming for solving multi-objective optimization problems. A practical, hands-on reference and text, Engineering;

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Cooperative Optimal Control of Hybrid Energy Systems

optimization, distributed optimization and distributed control approaches for tackling with security, economic and stability problem of the hybrid;

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Cooperative Optimal Control of Hybrid Energy Systems

optimization, distributed optimization and distributed control approaches for tackling with security, economic and stability problem of the hybrid;

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Hybrid Metaheuristics

readers to design and implement hybrid metaheuristics to solve complex optimization problems (continuous/discrete, mono-objectivemulti-objective;

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Intelligent Distributed Computing XII

intelligence, multi-agent systems, multi-criteria optimization and Deep/Shallow machine learning models, all of which are approached as technological;

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Multi-Objective Optimization Using Artificial Intelligence Techniques

Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and;

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Advances in Engineering Research

particle swarm optimization is presented and compared with existing Pareto dominance-based multi-objective techniques such as non-dominated sorting;

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Intelligent Scheduling of Robotic Flexible Assembly Cells

effective strategy for scheduling RFAC in a multi-product assembly environment, in which dynamic status and multi-objective optimization problems;

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Intelligent Scheduling of Robotic Flexible Assembly Cells

effective strategy for scheduling RFAC in a multi-product assembly environment, in which dynamic status and multi-objective optimization problems;

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Multiobjective Optimization

multi-objective situations exist; concentrating on a single goal limits the applicability of math programming models. Accordingly;

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Multi-objective Optimization

research in the last 10 years, spurred by the new and effective techniques for multi-objective optimization. In order to capture this renewed;

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Parallel and Distributed Processing Techniques and Applications

Parallel and Distributed Processing Techniques and Applications is a compendium of articles and papers that were presented at PDPTA '14, an;

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Parallel and Distributed Processing Techniques and Applications

Parallel and Distributed Processing Techniques and Applications is a compendium of articles and papers that were presented at PDPTA '13, an;

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Concurrent And Distributed Computing In Java

of two parts. The first part deals with techniques for programming in shared-memory based systems. The book covers concepts in Java such as;

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Nested algorithms for optimal reservoir operation and their embedding in a decision support platform

Reservoir operation is a multi-objective optimization problem, and is traditionally solved with dynamic programming (DP) and stochastic;

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Nested Algorithms for Optimal Reservoir Operation and Their Embedding in a Decision Support Platform

Reservoir operation is a multi-objective optimization problem, and is traditionally solved with dynamic programming (DP) and stochastic;

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Swarm Intelligence Based Optimization

Based Optimization, ICSIBO 2016, held in Mulhouse, France, in June 2016. The 9 full papers presented were carefully reviewed and selected from;

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