Multi-objective optimization with adjusted PSO method on example of cutting process of hardened 18CrMo4 steel

• Autorzy: Stryczek R. , Pytlak B.

Warianty tytułu

PL

Optymalizacja wielokryterialna skorygowaną metodą PSO na przykładzie procesu skrawania stali 18CrMo4 w stanie zahartowanym

• Języki publikacji: EN PL

Abstrakty

EN

In this paper a Modified Particle Swarm Optimization (PSO) method for multi-objective (MO) problems with a discrete decision space is proposed. In the PSO method the procedure to determine inertia weight, learning factor and social factor is modified. In addition, both an elitism strategy and innovative deceleration mechanism preventing the particles from going beyond the limits of decision space are introduced. The proposed approach has been applied to a series of currently used test functions as well as to optimization problems connected with finish hard turning operation, where the obtained results have been compared with those obtained by means of Genetic Algorithms (GA). The results indicate that the proposed approach is relatively quick, and thus it is highly competitive with other optimization methods. The authors have obtained a very good diversity, convergence and a maximum range of the Pareto front in the criteria space. In order to assess the quality of the generated Pareto set for each of presented examples, a rating has been determined based on the entropy measurement and inverted generational distance (IGD).

PL

W pracy zaproponowano zmodyfikowaną metodę optymalizacji wielocząsteczkowej (PSO) dla problemów optymalizacji wielokryterialnej z dyskretną przestrzenią decyzyjną. W metodzie PSO zmieniono sposób określania momentu bezwładności, współczynnika uczenia oraz współczynnika społecznego. Dodatkowo wprowadzono elitaryzm oraz innowacyjny mechanizm hamowania cząstek chroniący je przed przekraczaniem dopuszczalnych granic przestrzeni decyzyjnej. Zaproponowane podejście zostało zweryfikowane na szeregu aktualnych funkcjach testowych oraz problemie optymalizacji procesu skrawania stali 18CrMo4 w stanie zahartowanym, gdzie porównano je z wynikami uzyskanymi za pomocą algorytmów genetycznych (GA). Uzyskane wyniki wskazują, że zaproponowane podejście jest względnie szybkie i wysoce konkurencyjne w stosunku do innych metod optymalizacji. Autorzy uzyskali bardzo różnorodne, zbieżne i w pełnym zakresie przebiegi frontu Pareto w przestrzeni kryteriów. W celu oceny jakości wygenerowanego zbioru Pareto dla każdego z prezentowanych przykładów wyznaczono ocenę opartą na pomiarze entropii oraz wskaźnika jakości IGD.

Słowa kluczowe

EN

hard turning; particle swarm optimization (PSO) method; evolutionary computations; multi-objective optimization; entropy

PL

toczenie na twardo; metoda optymalizacji wielocząsteczkowej (PSO); obliczenia ewolucyjne; optymalizacja wielokryterialna; entropia

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2014
• Tom: Vol. 16, no. 2
• Strony: 236--245
• Opis fizyczny: Bibliogr. 29 poz., rys., tab.

Twórcy

autor

Stryczek R.

• Department of Manufacturing Technology and Automation University of Bielsko-Biala, 43-309 Bielsko-Biała, ul. Willowa 2, Poland

autor

Pytlak B.

• Department of Manufacturing Technology and Automation University of Bielsko-Biala, 43-309 Bielsko-Biała, ul. Willowa 2, Poland

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