A random generator of resource-constrained multi-project network problems

Tyson R. Browning, Ali A. Yassine

    Research output: Contribution to journalArticlepeer-review

    47 Scopus citations

    Abstract

    Many scheduling problems in project management, manufacturing, and elsewhere require the generation of activity networks to test proposed solution methods. Single-network generators have been used for the resource - constrained project scheduling problem (RCPSP). Since the first single-network generator was proposed in 1993, several advances have been reported in the literature. However, these generators create only one network or project at a time; they cannot generate multi-project problems to desired specifications. This paper presents the first multinetwork problem generator. It is especially useful for investigating the resource-constrained multi-project scheduling problem (RCMPSP), where a controlled set of multi-project test problems is crucial for analyzing the performance of solution methods. In addition to the single-project characteristics handled by existing network generators-such as activity duration, resource types and usage, and network size, shape, and complexity-the proposed generator produces multi-project portfolios with controlled resource distributions and amounts of resource contention. To enable the generation of projects with desired levels of network complexity, we also develop several theoretical insights on the effects of network topology on the probability of successful network generation. Finally, we generate 12,320 test problems for a full-factorial experiment and use analysis of means to conclude that the generator produces "near-strongly random" problems. Fully "strongly random" problems require much greater computational expense.

    Original languageEnglish
    Pages (from-to)143-161
    Number of pages19
    JournalJournal of Scheduling
    Volume13
    Issue number2
    DOIs
    StatePublished - Apr 2010

    Keywords

    • Multi-project scheduling
    • Network complexity
    • Project scheduling
    • Random network generator
    • Resource constraints

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