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A global optimization algorithm for signomial geometric problem
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DOI：10.1016/j.orp.2026.100401.png)
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Abstract
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• A branch-and-bound algorithm for global optimization of signomial geometric programming problems is improved based on duality theory. • A new upper-bounding strategy based on the condensation technique is incorporated as a local search component, improving bound refinement and accelerating convergence. • An initialization method is proposed, combining optimal solutions and adaptive sampling within a spherical region, aiming to enhance search efficiency. • Numerical experiments on benchmark problems confirm that the proposed method consistently attains global optimal solutions. • The algorithm exhibits strong computational performance, with a low number of iterations and execution time below 8 s for all tested instances.
Keywords:
Geometric programming
Global optimization
Mathematical programming
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