A new foraging-based algorithm for online scheduling

While much work exists on scheduling, literature in the subfield of online scheduling remains sparse. As with many problems, online scheduling has parallels with natural phenomena. Specifically, online scheduling can be seen in the division of labour among colony insects, such as ants. Although multiple different biological models exist for division of labour, the only one to have been applied in online scheduling is the reinforced threshold model, for instance in the form of the ant task allocation (ATA) algorithm. However, it is neither known how it compares to other models, nor in which applications any of them excel. This paper studies the foraging for work (FFW) model as a possible alternative. To do so, an algorithmic description of the FFW model is introduced, and it is compared with the ATA algorithm on the truck painting problem. For this problem, tasks of various types are scheduled in a flowshop with multiple identical machines in an online fashion. FFW is shown to be very effective at minimising setup time, which is incurred when switching to tasks of different types. Furthermore, this allows FFW to outperform the threshold based approaches when the scheduling environment is placed under heavy load.

[1]  G. Theraulaz,et al.  Response threshold reinforcements and division of labour in insect societies , 1998, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[2]  Mauro Birattari,et al.  An Insect-Based Algorithm for the Dynamic Task Allocation Problem , 2005, Künstliche Intell..

[3]  Guy Theraulaz,et al.  Dynamic Scheduling and Division of Labor in Social Insects , 2000, Adapt. Behav..

[4]  N. Franks,et al.  Studies of the division of labour: neither physics nor stamp collecting , 1997, Animal Behaviour.

[5]  B. Goodwin,et al.  A Parallel Distributed Model of the Behaviour of Ant Colonies , 1992 .

[6]  Stephen F. Smith,et al.  Wasp-like Agents for Distributed Factory Coordination , 2004, Autonomous Agents and Multi-Agent Systems.

[7]  Chris Tofts.  Algorithms for task allocation in ants. (A study of temporal polyethism: Theory) , 1993 .

[8]  Nikolaus Correll,et al.  Modeling multi-robot task allocation with limited information as global game , 2016, Swarm Intelligence.

[9]  L. Keller,et al.  An Evolutionary Perspective on Self-Organized Division of Labor in Social Insects , 2011 .

[10]  Chris Tofts,et al.  Foraging for work: how tasks allocate workers , 1994, Animal Behaviour.

[11]  J. Traniello,et al.  Ecology, evolution and division of labour in social insects , 1997, Animal Behaviour.

[12]  Cihan H. Dagli,et al.  Real-time routing in flexible flow shops: a self-adaptive swarm-based control model , 2007 .

[13]  Yutaka Nakamura,et al.  Adaptive foraging for simulated and real robotic swarms: the dynamical response threshold approach , 2016, Swarm Intelligence.

[14]  R. E. Page,et al.  Temporal polyethism in social insects is a developmental process , 1994, Animal Behaviour.

[15]  Shervin Nouyan,et al.  Agent-Based Approach to Dynamic Task Allocation , 2002, Ant Algorithms.

[16]  J. Fewell,et al.  Models of division of labor in social insects. , 2001, Annual review of entomology.

[17]  E. Bonabeau,et al.  Quantitative study of the fixed threshold model for the regulation of division of labour in insect societies , 1996, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[18]  S. Beshers,et al.  Division of labour and ‘foraging for work’: simulating reality versus the reality of simulations , 1997, Animal Behaviour.

[19]  Laurent Keller,et al.  Evolution of self-organized division of labor in a response threshold model , 2012, Behavioral Ecology and Sociobiology.

[20]  Sanja Petrovic,et al.  SURVEY OF DYNAMIC SCHEDULING IN MANUFACTURING SYSTEMS , 2006 .

[21]  C. Plowright,et al.  Elitism in Social Insects: A Positive Feedback Model , 2019, Interindividual Behavioral Variability in Social Insects.

[22]  O. Kittithreerapronchai,et al.  Do ants paint trucks better than chickens? Markets versus response thresholds for distributed dynamic scheduling , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[23]  dominulus Christ.  Self-organization of Hierarchies in Animal Societies: The Case of the Primitively Eusocial Wasp Polsites dominulus Christ , 2022 .

[24]  Stephen F. Smith,et al.  Is Scheduling a Solved Problem , 2005 .

[25]  Guy Theraulaz,et al.  Task differentiation in Polistes wasp colonies: a model for self-organizing groups of robots , 1991 .

[26]  Guy Theraulaz,et al.  Self-organization of hierarchies in animal societies: the case of the primitively eusocial waspPolistes dominulusChrist , 1995 .