This thesis explores competitive facility location planning through the lens of leader-follower models, leveraging advanced bilevel optimization techniques to address hierarchical decision- making scenarios. The foundational principles of competitive facility location planning and bilevel optimization are presented in detail, providing the reader with a comprehensive understanding necessary for the context and methodology of this work.

Central to this study is the adaptation of a solution algorithm based on Karush-Kuhn- Tucker conditions. Originally developed for production program planning, this algorithm is applied to reformulate mixed-integer bilevel linear problems involving discrete follower decisions, despite the inherent challenges posed by the non-convexity of such problems.

During the analysis, a critical limitation in the existing approach was identified. This limitation stems from the handling of a binary auxiliary variable, which represents inter- actions between the leader and follower decisions. To address this issue, the model was carefully revised to eliminate the dependency on this variable while preserving the integrity of the decision-making process. These modifications enabled the solution algorithm to be effectively applied and rigorously tested on the revised model.

The findings demonstrate that the algorithm performs robustly and efficiently within the revised framework, delivering consistent results across a diverse range of test cases. This demonstrates its applicability and reliability for addressing competitive facility location problems.