Vol.11, No 1, 2013 pp. 29-44
UDC
519.863; 621.7.01
COMPARISON OF META-HEURISTIC ALGORITHMS FOR SOLVING MACHINING OPTIMIZATION PROBLEMS
Miloš Madić, Danijel Marković, Miroslav Radovanović
University of Niš, Faculty of Mechanical Engineering, Niš, Serbia
Since optimization of the machining parameters not only increases machining efficiency and economics, but it also enhances the end product quality, this topic is still the subject of many studies. The selection of the optimal machining parameters is often performed in a two-stage approach, i.e. mathematical modeling of machining performance and optimization using an optimization method. Among the traditional optimization methods, in recent years, the modern meta-heuristic algorithms are being increasingly applied to solving machining optimization problems. Their ability to deal with complex, multi-dimensional and ill-behaved optimization problems has made them choice number one by most researchers and practitioners. In the present study, an attempt is made to compare the optimization results of different meta-heuristic algorithms applied to solving machining optimization problems. Four meta-heuristic algorithms are taken into consideration, namely, real coded genetic algorithm (RCGA), simulated annealing (SA), improved harmony search algorithm (IHSA) and cuckoo search algorithm (CSA). These meta-heuristic algorithms are applied to searching for optimal combinations of different machining parameters for five case studies taken from the literature. The optimization results obtained by applying RCGA, SA, IHSA and CSA for parametric optimization of these machining processes are compared with those derived by the past researchers.
Key words:
Machining, Optimization, Meta-heuristic Algorithms
POREĐENJE META-HEURISTIČKIH ALGORITAMA ZA REŠAVANJE PROBLEMA OPTIMIZACIJE PARAMETRA OBRADE
Optimizacija parametara obrade ne utiče samo da efikasnost i ekonomičnost obrade već i na finalni kvalitet proizvoda, pa samim tim ova tema je još uvek predmet izučavanja mnogih studija. Izbor optimalnih parametara obrade često se obavlja u dve faze, odnosno matematičkim modeliranjem performansi obrade i optimizacijom pomoću optimizacionih metoda. Njihova mogućnost da rešavaju složene i višediemzionalne optimizacione probleme učinila je da postanu veoma popularan izbor od strane većine istraživača. U ovom radu, autori su uporedili rezultate optimizacije raličitih meta-heurističkih algoritama koji su primenjeni na rešavanje optimizacionih problema obrade. Razmatrana su četiri meta-heuristička algoritma i to: realno kodirani genetski algoritam, simulirano kaljenje, poboljšani algoritam harmonijskog pretraživanja i algoritam kukavice. Pomoću ovih meta-heurističkih algoritmama su tražene optimalne kombinacije različitih parametra obrade za pet studija slučaja uzetih iz literature. Rezultati optimizacije, dobijeni pomoću prethodno navedenih pet meta-heuristička algoritma za parametrsku optimizaciju procesa obrade, su upoređeni sa rezultatima poslednjih istraživanja.
Ključne reči:
mašinska obrada, optimizacija, meta-heuristički algoritmi
