W pracy zaproponowano nowatorskie podejście do analizy algorytmów stadnych na przykładach algorytmów: pszczelego oraz kukułki, w kontekście problemu szeregowania zadań dla modelu przepływowego (permutacyjny flow shop).
Obok wprowadzenia w modele szeregowania zadań z jednej oraz algorytmy stadne z drugiej strony, praca porusza bardzo ważną problematykę wyznaczania liczby iteracji w zależności od przyjętego sposobu definiowania sąsiedztwa w przestrzeniach kombinatorycznych.
Analizę przeprowadzono dla algorytmów zrównoleglonych zaimplementowanych w języku Scala w oparciu o testy zespołu Erica Taillarda.
Boids algorithms in optimization of flow shop models
This thesis takes the reader on the fascinating journey through the world of task scheduling problems. First, it introduces the most common parallel flow models: flow shop, job shop and open shop - in their deterministic and stochastic versions. We focus here on proofs that they belong to NP-complete complexity class.
Then we move to the herd (known as 'boids' also) algorithms realm. This part presents the main requirements for every stochastic algorithm and describes in details two representatives of this algorithms family:
bee and cuckoo algorithms.
Next, we deliberate about neighborhoods, the combinatorial space of their solution models, and how those models influence the objective function shape.
We discuss the methods of computing iteration numbers for the above algorithms using Chernoff inequality and coupled Markov chains.
The conclusions are then used in concrete implementations, we have a practical implementation in Scala. The main idea is funded on the actors model (similar to the agents model) which allows for asynchronous, multithreaded computations. Scala provides strong support for distributed computations, and was thusly chosen as the implementation language. Finally, we present the results of the application runs on Taillard's test for permutative parallel flow shop model.
