October 13, 2025Open Access

Parameter-Adaptive Dynamic Pricing

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This approach introduces a parameter-adaptive method for dynamic pricing, enhancing flexibility and reducing regret in unknown demand scenarios.

The Parameter-Adaptive Dynamic Pricing algorithm improves regret bounds compared to existing methods, enhancing demand management.
Numerical experiments demonstrate how effectively the algorithm handles unknown demand parameters, validating its practical utility.
The adaptive method utilizes a linear bandit structure to manage regret efficiently while partitioning the demand function’s domain.
This study highlights the flexibility of the algorithm by allowing for extensions involving contextual information for dynamic pricing.

Gong et al. (2025) studied this question.

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October 13, 2025Open Access

View Full Paper

Ask AI

Bookmark

Authors

This approach introduces a parameter-adaptive method for dynamic pricing, enhancing flexibility and reducing regret in unknown demand scenarios.

The Parameter-Adaptive Dynamic Pricing algorithm improves regret bounds compared to existing methods, enhancing demand management.
Numerical experiments demonstrate how effectively the algorithm handles unknown demand parameters, validating its practical utility.
The adaptive method utilizes a linear bandit structure to manage regret efficiently while partitioning the demand function’s domain.
This study highlights the flexibility of the algorithm by allowing for extensions involving contextual information for dynamic pricing.

Gong et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark