• No results found

constrained single-objective approach

Multi Objective Constrained Optimization using Discrete Mechanics and NSGA II Approach

Multi Objective Constrained Optimization using Discrete Mechanics and NSGA II Approach

... in one single simulation run due to their population-approach. EAs are ideal for solving multi-objective optimization problems. Although there exist a number of multi-objective evolutionary ...

8

Approach of Solving Dual Resource Constrained Multi-Objective Flexible Job Shop Scheduling Problem Based on MOEA/D

Approach of Solving Dual Resource Constrained Multi-Objective Flexible Job Shop Scheduling Problem Based on MOEA/D

... This paper proposes a scheduling model for DRCFJSPs that minimizes the maxi- mum completion time, minimizes the processing equipment load, and minimizes the production cost. It uses the MOEA/D algorithm framework ...

15

Optimized task scheduling based on hybrid symbiotic organisms search algorithms for cloud computing environment

Optimized task scheduling based on hybrid symbiotic organisms search algorithms for cloud computing environment

... no single solution which is optimal with respect to all objectives, but a set of trade-off solutions called Pareto front (Tao et ...(weighted) approach is the common method for solving ...

50

Linear Antenna Array Synthesis with Constrained Multi-Objective Differential Evolution

Linear Antenna Array Synthesis with Constrained Multi-Objective Differential Evolution

... decomposition approach for converting the problem of approximation of the Pareto Fronts (PF) into a number of single objective optimization ...the single-objective approaches, the MO ...

25

An Advanced Ant Colony Algorithm for Constrained Multi objective Optimization Problem

An Advanced Ant Colony Algorithm for Constrained Multi objective Optimization Problem

... into single-objective by linear weighting method or sequential ...This approach is simple, but it cannot well balance multiple optimization goals with conflict ...the constrained ...

9

Stopping Criteria for a Constrained Single-Objective Particle Swarm Optimization Algorithm

Stopping Criteria for a Constrained Single-Objective Particle Swarm Optimization Algorithm

... expensive objective functions, the perfor- mance of several stopping criteria that react adaptively to the state of an optimization run is evaluated for a Particle Swarm Optimization algorithm in this ...a ...

10

Fuzzy Programming Approach for a Multi-objective Single Machine Scheduling Problem with Stochastic Processing Time

Fuzzy Programming Approach for a Multi-objective Single Machine Scheduling Problem with Stochastic Processing Time

... based approach for solving a mixed-integer model of a single machine scheduling problem minimizing the total weighted flow time and total weighted ...based approach to solve the extended mathematical ...

5

A hybrid particle swarm evolutionary algorithm for constrained multi-objective optimization

A hybrid particle swarm evolutionary algorithm for constrained multi-objective optimization

... In the following of this section let A, B represent two sets of Pareto optimal solutions in the decision space, and P A, P B denote the corresponding Pareto solution sets in the objective space. We propose three ...

18

Single Objective Single Function Criteria for Selection of Manufacturing Method

Single Objective Single Function Criteria for Selection of Manufacturing Method

... a single objective and a single ...a single objective, function and a method ...a single objective, a single function and a method ...a single ...

9

A learning guided multi objective evolutionary algorithm for constrained portfolio optimization

A learning guided multi objective evolutionary algorithm for constrained portfolio optimization

... In recent years, many publications had discussed the portfolio optimization problems with multi-objective evolutionary algorithms by considering a subset of the real-world constraints. Diosan [22] and Mishra et ...

33

Applying a global optimisation algorithm to Fund of Hedge Funds portfolio optimisation

Applying a global optimisation algorithm to Fund of Hedge Funds portfolio optimisation

... In PGSL, as with almost all of the global search optimisation algorithms, both the linear and non-linear constraints are defined as penalty functions added to the objective function and hence are soft constraints ...

24

Multi Objective UAS Flight Management in Time Constrained Low Altitude Local Environments

Multi Objective UAS Flight Management in Time Constrained Low Altitude Local Environments

... This paper has presented a new framework for multi-objective flight management in time constrained low altitude local environments. A finite length of time defined as the limited decision window was ...

14

Constrained  PRFs  for  Bit-fixing (and  More)  from  OWFs  with  Adaptive  Security   and  Constant  Collusion  Resistance

Constrained PRFs for Bit-fixing (and More) from OWFs with Adaptive Security and Constant Collusion Resistance

... two constrained key ...one constrained key query is not permitted is that it would reveal all of the underlying PRF keys, while there would still be constrained ...

28

Chapter 1_SPM.ppt

Chapter 1_SPM.ppt

... T – time constrained: there is defined point in time by which the objective should be achieved.. Goals/sub-objectives[r] ...

26

A Penalty Function Algorithm with  Objective Parameters and Constraint  Penalty Parameter for Multi Objective  Programming

A Penalty Function Algorithm with Objective Parameters and Constraint Penalty Parameter for Multi Objective Programming

... Abstract In this paper, we present an algorithm to solve the inequality constrained multi-objective programming MP by using a penalty function with objective parameters and constraint pe[r] ...

10

Single and multi-objective optimization - a comparative analysis

Single and multi-objective optimization - a comparative analysis

... Pareto actually introduced an order relation to find an optimal solution to a multi-objective problem like in one dimension, the ordering of real numbers is used to find an optimal solution. 2.1. Single and ...

18

Optimization of Wire EDM with Brass wire as electrode on HCHCr steel by using Single Objective Taguchi Approach

Optimization of Wire EDM with Brass wire as electrode on HCHCr steel by using Single Objective Taguchi Approach

... using single objective Taguchi optimization technique, optimal value for MRR and Surface Roughness has been obtained by varying the machiningparameters pulse on time, pulse off time and wire ...

9

Adaptively  Single-Key  Secure  Constrained  PRFs  for  NC1

Adaptively Single-Key Secure Constrained PRFs for NC1

... (constraint-hiding) single-key secure CPRF for NC 1 that achieves a weaker form of adaptive security where adversaries are allowed to send logarithmically many evaluation queries before a constraining query as ...

39

Optimal Power Flow By Particle Swarm Optimization For Reactive Loss Minimization

Optimal Power Flow By Particle Swarm Optimization For Reactive Loss Minimization

... specific objective in operating a power system network is optimized (maximizing or minimizing) with respect to the power system constraints, dictated by the electrical ...thesis single objective OPF ...

6

TOPSIS APPROACH TO CHANCE CONSTRAINED MULTI - OBJECTIVE MULTI- LEVEL QUADRATIC PROGRAMMING PROBLEM

TOPSIS APPROACH TO CHANCE CONSTRAINED MULTI - OBJECTIVE MULTI- LEVEL QUADRATIC PROGRAMMING PROBLEM

... TOPSIS approach to solve chance constrained multi-level multi objective quadratic programming ...proposed approach, firstly, we have transformed chance constraints into equivalent ...

18

Show all 10000 documents...

Related subjects