Maximising the net present value of project schedules using CMSA and parallel ACO

Dhananjay Thiruvady, Christian Blum, Andreas T. Ernst

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11 Citations (Scopus)


This study considers the problem of resource constrained project scheduling to maximise the net present value. A number of tasks must be scheduled within a fixed time horizon. Tasks may have precedences between them and they use a number of common resources when executing. For each resource, there is a limit, and the cumulative resource requirements of all tasks executing at the same time must not exceed the limits. To solve this problem, we develop a hybrid of Construct, Merge, Solve and Adapt (CMSA) and Ant Colony Optimisation (ACO). The methods are implemented in a parallel setting within a multi-core shared memory architecture. The results show that the proposed algorithm outperforms the previous state-of-the-art method, a hybrid of Lagrangian relaxation and ACO.

Original languageEnglish
Title of host publicationHybrid Metaheuristics
Subtitle of host publication11th International Workshop, HM 2019, Proceedings
EditorsMaria J. Blesa Aguilera, Christian Blum, Pedro Pinacho-Davidson, Julio Godoy del Campo, Haroldo Gambini Santos
Place of PublicationCham Switzerland
Number of pages15
ISBN (Electronic)9783030059835
ISBN (Print)9783030059828
Publication statusPublished - 1 Jan 2019
EventInternational Workshop on Hybrid Metaheuristics, 2019 - Concepción, Chile
Duration: 16 Jan 201918 Jan 2019
Conference number: 11th

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Workshop on Hybrid Metaheuristics, 2019
Abbreviated titleHM 2019
Internet address


  • Ant Colony Optimisation
  • Construct
  • Merge
  • Net present value
  • Project scheduling
  • Solve & Adapt

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