Evolutionary robust optimization in production planning -- interactions between number of objectives, sample size and choice of robustness measure

DOI10.1016/j.cor.2016.06.020zbMath1391.90652OpenAlexW2475112345MaRDI QIDQ1652171

Y. Aharonov

Publication date: 11 July 2018

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://www.research.manchester.ac.uk/portal/en/publications/evolutionary-robust-optimization-in-production-planning--interactions-between-number-of-objectives-sample-size-and-choice-of-robustness-measure(f7f88580-485a-42be-a94f-2ecf055a8d21).html

zbMATH Keywords

simulation-based optimizationproduction planningrobust optimizationuncertainty modellingevolutionary multi-objective optimization

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59) Production models (90B30) Inventory, storage, reservoirs (90B05)

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A largest empty hypersphere metaheuristic for robust optimisation with implementation uncertainty ⋮ Non-convex multiobjective optimization under uncertainty: a descent algorithm. Application to sandwich plate design and reliability ⋮ A stochastic multiple gradient descent algorithm ⋮ Particle swarm metaheuristics for robust optimisation with implementation uncertainty ⋮ Hybrid stochastic and robust optimization model for lot-sizing and scheduling problems under uncertainties ⋮ Automatic generation of algorithms for robust optimisation problems using grammar-guided genetic programming ⋮ Introducing Robust Evolutionary Optimization in Noisy Fractional-Order Systems ⋮ Incorporating decision-maker's preferences into the automatic configuration of bi-objective optimisation algorithms

Uses Software

• SPOT

Cites Work

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• GP-DEMO: differential evolution for multiobjective optimization based on Gaussian process models
• Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations
• Robust optimization of the 0-1 knapsack problem: balancing risk and return in assortment optimization
• Using Choquet integral as preference model in interactive evolutionary multiobjective optimization
• The weighted sum method for multi-objective optimization: new insights
• A new mutation operator for real coded genetic algorithms
• Evolutionary multi-objective optimization in uncertain environments. Issues and algorithms
• A real coded genetic algorithm for solving integer and mixed integer optimization problems
• An efficient constraint handling method for genetic algorithms
• Recent advances in robust optimization: an overview
• Evolutionary optimisation of noisy multi-objective problems using confidence-based dynamic resampling
• A new crossover operator for real coded genetic algorithms
• Uncertain multiobjective traveling salesman problem
• The Attainment-Function Approach to Stochastic Multiobjective Optimizer Assessment and Comparison
• Exploratory Analysis of Stochastic Local Search Algorithms in Biobjective Optimization
• On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other

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