A new multi-section based technique for constrained optimization problems with interval-valued objective function

DOI10.1016/j.amc.2013.09.042zbMath1334.90156OpenAlexW2073412269MaRDI QIDQ275782

Samiran Karmakar, Asoke Kumar Bhunia

Publication date: 26 April 2016

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2013.09.042

zbMATH Keywords

decision theoryinterval optimizationinterval mathematicsinterval objective functioninterval order relations

Mathematics Subject Classification ID

Decision theory (91B06) Polyhedral combinatorics, branch-and-bound, branch-and-cut (90C57) Multi-objective and goal programming (90C29)

Related Items

Computing the range of values of real functions using B-spline form

Uses Software

• INTOPT_90

Cites Work

• On constrained optimization by interval arithmetic and interval order relations
• Optimal value bounds in nonlinear programming with interval data
• Interval oriented multi-section techniques for global optimization
• Multiobjective programming in optimization of interval objective functions -- a generalized approach
• Rigorous global search: continuous problems
• Heuristic rejection in interval global optimization
• Multisection in interval branch-and-bound methods for global optimization. II: Numerical tests
• Multisection in interval branch-and-bound methods for global optimization. I: Theoretical results
• On comparing interval numbers
• Ordering of intervals and optimization problems with interval parameters
• A numerical solution method to interval quadratic programming
• Generalized subinterval selection criteria for interval global optimization
• Multiobjective programming in optimization of the interval objective function
• Interval-arithmetic-oriented interval computing technique for global optimization
• Introduction to Interval Analysis
• Rigorous solution of linear programming problems with uncertain data
• Interpretation of inequality constraints involving interval coefficients and a solution to interval linear programming.
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