Optimizing project selection: a perspective from resource constraints. (2nd November 2017)

• Record Type: Journal Article
• Authors: Zhao, Tianyi; Huang, Xiaoxia
• Is Part Of: Optimization. Volume 66:Number 11(2017)
• Page Start: 1863
• Page End: 1878
• Publication Date: 2017-11-02
• Subjects: Project selection -- non-renewable resource -- renewable resource -- resource sharing -- genetic algorithm; Mathematical optimization -- Periodicals; 519.7
• DOI: 10.1080/02331934.2017.1317777
• Languages: English
• ISSNs: 0233-1934

Abstract

Abstract : In reality, projects usually consume complex resources. Making good use of the various resources is vital for optimal project selection and maximum profit earning. This paper proposes a new project selection model from the perspective of complex resource constraints. In the model, the resources are divided into non-renewable and renewable categories, and some resources of the two categories can both be shared by different projects. In addition, the paper considers the situation where the company has resources in stock and can purchase them in the marketplace if they are out of stock. The paper proves that the proposed model which considers renewable resource and resource sharing produces higher profit than the ones that do not consider renewable resource and resource sharing. To solve the complex model problem, an improved genetic algorithm is presented. For the sake of illustration, a case study is provided.