Metaheuristic Algorithms for Multi-mode Multi-project Scheduling with the Objective of Positive Cash flow Balance

Yukang He, Jingwen Zhang, Zhengwen He

Research output: Contribution to journalArticlepeer-review


This paper investigates the problem of how to achieve a positive cash flow balance by multimode multiproject scheduling, in which a contractor must implement multiple projects concurrently, and activities can be performed with one of several alternative modes. First, based on formulating cash flows for the projects, we construct an optimization model that can minimize the maximum gap between accumulative cash outflow and cash inflow, thus balancing cash flow positively by arranging optimal execution modes and start times for activities. Then, we prove the NP-hardness of the studied problem and design two metaheuristic algorithms, namely, tabu search (TS) and simulated annealing (SA), which search the desirable solutions in nested and mixed ways, respectively. Finally, taking the multistart iterative improvement (MSII) as comparison algorithm, the performance of the two algorithms developed is evaluated through a computational experiment performed on a data set generated randomly. From the research results, the following conclusions are drawn. The TS and SA are more suitable for solving the smaller and larger problems, respectively, while the nested searching structure could enhance the algorithm's efficiency. With increases in the advance payment proportion, the number of milestone activities, the client's payment proportion, or the project deadline, the contractor's maximal cash flow gap decreases.

Original languageEnglish
Article number8853254
Pages (from-to)157427 - 157436
Number of pages10
JournalIEEE Access
Early online date30 Sep 2019
Publication statusPublished - 1 Jan 2020

Bibliographical note

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  • Project scheduling
  • metaheuristic algorithm
  • multimode multiproject context
  • optimization model
  • positive cash flow balance


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