Abstract
Due to long lead times, uncertain outcomes and lack of enough historical data, pharmaceutical research and development (R &D) portfolio selection is a often very complex decision issue. The aim of this paper is to investigate pharmaceutical R &D portfolio selection with unavailable and unreliable project information, where the borrowed capital is allowed. Based on fuzzy set theory, we propose a pharmaceutical R &D portfolio optimization model with minimum borrowed capital by taking into account corporate strategy in developing new products, scarcity of resources, lack of investment budget and cardinality constraint. In the proposed model, the pharmaceutical R &D company is assumed to achieve the objectives of maximizing terminal wealth and minimizing the cumulative borrowed capital over the whole investment horizon. Then, we transform the proposed bi-objective model into the corresponding single-objective model by using the weighted sum approach and employ the modified artificial bee colony (MABC) algorithm to solve the transformed model. Finally, we provide a numerical example to illustrate the application of our model.
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