Uyumsuz iş setlerini içeren karmaşık montaj hattı dengeleme problemi için bastırılmamış sınıflandırmalı karınca koloni optimizasyonu algoritması

İki-taraflımontaj hatları otomotiv endüstrisinde otobüs, kamyon ve otomobil gibi genişhacimli ürünlerin üretiminde yoğunlukla kullanılmaktadır. Karışık modellihatlar ise üreticilere müşterilerin kişiselleştirilmiş talebini uygun maliyetleve istenen kalitede ulaştırmak için yardımcı olmaktadır. Bu çalışma uyumsuz işgruplarını içeren karışık-modelli iki taraflı montaj hatlarını konu almaktadırve hat etkinliğini maksimize etmek için birbiriyle çelişen iki amacı (çevrimzamanı ve istasyon sayısı) minimize eden yeni bir yöntem önermektedir. Böylebir yaklaşım montaj hattı alanında tip-E olarak adlandırılan probleme işaretetse de önerilen bastırılmamış sınıflandırmalı karınca koloni algoritması(NSACO) diğer çözümleri her iki amaç açısından da bastıran çözüm setisunmaktadır (pareto yüzey çözümler). Çözümler arasından en yüksek hatetkinliğine sahip olanı en iyi çözüm olarak belirlenmektedir. İki farklı çözümher iki amaç açısından da aynı değerlere sahip olduğu zaman, ilave birperformans kriteri uygulanmaktadır. Her iki amaç da aynı değerlere sahip olduğuzaman daha düzgün iş yükü dağılımına sahip olan çözüm tercih edilmektedir.NSACO tanımlanmıştır ve çalışma prensibi bir sayısal örnek üzerindenanlatılmıştır. Algoritmanın performansı, uyumsuz iş seti kısıtlarını dikkatealarak ve almayarak iki durum altında test edilmiştir ve araştırma sonuçlarıilk defa sunulmuştur. Sonuçlar göstermektedir ki NSACO ümit verici çözümkapasitesine sahiptir.

A nondominated sorting ant colony optimization algorithm for complex assembly line balancing problem incorporating incompatible task sets

Two-sidedassembly lines are heavily used in automotive industry for producinglarge-sized products such as buses, trucks and automobiles. Mixed-model lineshelp manufacturers satisfy customized demands at a reasonable cost with desiredquality. This paper addresses to mixed-model two-sided lines incorporatingincompatible task groups and proposes a new method for minimizing twoconflicting objectives, namely cycle time and the number of workstations, tomaximize line efficiency. While such an approach yields to a so-called type-Eproblem in the line balancing domain, the proposed nondominated sorting antcolony optimization (NSACO) approach provides a set of solutions dominatingothers in terms of both objectives (pareto front solutions). The solution whichhas the highest line efficiency among pareto front solutions is then determinedas the best solution. An additional performance criterion is also applied whentwo different solutions have the same values for both objectives. The solutionwhich has the smoother workload distribution is favoured when both criteria arethe same. NSACO is described and a numerical example is provided to exhibit itsrunning mechanism. The performance of the algorithm is tested through testproblems in two conditions, i.e. incompatible task sets are considered and notconsidered, and computational results are presented for the first time. Theresults indicate that NSACO has a promising solution capacity.

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