A combinatorial optimization model for enterprise patent transfer

Abstract

Enterprises need patent transfer strategies to improve their technology management. This paper proposes a combinatorial optimization model that is based on intelligent computing to support enterprises' decision making in developing patent transfer strategy. The model adopts the Black---Scholes Option Pricing Model and Arbitrage Pricing Theory to estimate a patent's value. Based on the estimation, a hybrid genetic algorithm is applied that combines genetic algorithms and greedy strategy for the optimization purpose. Encode repairing and a single-point crossover are applied as well. To validate this proposed model, a case study is conducted. The results indicate that the proposed model is effective for achieving optimal solutions. The combinatorial optimization model can help enterprise promote their benefits from patent sale and support the decision making process when enterprises develop patent transfer strategies.