Helper-objectives: Using multi-objective evolutionary algorithms for single-objective optimisation

DOI10.1007/s10852-005-2582-2zbMath1073.68079OpenAlexW4248462665MaRDI QIDQ1774625

Mikkel T. Jensen

Publication date: 17 May 2005

Published in: JMMA. Journal of Mathematical Modelling and Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10852-005-2582-2

zbMATH Keywords

job shop schedulingtravelling salesman problems

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59) Combinatorial optimization (90C27) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (13)

Using multi-objective evolutionary algorithms for single-objective constrained and unconstrained optimization ⋮ Plateaus can be harder in multi-objective optimization ⋮ Multi-objectivization via decomposition: an analysis of helper-objectives and complete decomposition ⋮ Multi-objectivization, fitness landscape transformation and search performance: a case of study on the HP model for protein structure prediction ⋮ Constraint-handling through multi-objective optimization: the hydrophobic-polar model for protein structure prediction ⋮ Using multi-objective evolutionary algorithms for single-objective optimization ⋮ Evolutionary optimization: pitfalls and booby traps ⋮ Graph Consistency as a Graduated Property ⋮ Bi-goal evolution for many-objective optimization problems ⋮ Multi-objectivization relaxes multi-funnel structures in single-objective NK-landscapes ⋮ A penalty-based multi-objectivization approach for single objective optimization ⋮ Selection of Auxiliary Objectives Using Landscape Features and Offline Learned Classifier ⋮ Analysis of Solution Quality of a Multiobjective Optimization-Based Evolutionary Algorithm for Knapsack Problem

Cites Work

• New Search Spaces for Sequencing Problems with Application to Job Shop Scheduling
• On the Average Number of Maxima in a Set of Vectors and Applications
• Algorithms for Solving Production-Scheduling Problems
• Subcost-guided search -- experiments with timetabling problems
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