Energy-Based Scheduling Optimization To Minimize The Total Energy Consumption And The Total Tardiness In A Single Machine Manufacturing System With The Sequence-Dependent Setup Times

Year 2024, , 169 - 183, 29.02.2024

Elif Tarakçı , Abdül Halim Zaim , Oğuzhan Öztaş

https://doi.org/10.2339/politeknik.1075096

Abstract

Nowadays, reducing energy consumption is an important target for energy-intensive manufacturing systems due to many reasons such as global warming, legal obligations and lowering company expenses. Therefore, this paper focuses on energy-based scheduling problem in manufacturing systems. A mixed-integer nonlinear programming (MINLP) model is developed for a single machine scheduling problem with the sequence-dependent setup times and different arrival times in order to minimize the total energy consumption and the total tardiness. An energy-based genetic optimization (EGOP) method is proposed by adopting the genetic algorithm (GA) approach, which is a heuristic method to solve the problem. The objective values and the computation times are compared with the analytical solution and the General Algebraic Modeling System (GAMS) solution so as to evaluate the performance of the proposed method. As a result, it is seen that the proposed EGOP method provides effective results.

Keywords

Energy consumption, genetic algorithm, job scheduling, sequence-dependent setup time.

Sıra Bağımlı Hazırlık Süreli Tek Makineli Üretim Sisteminde Toplam Enerji Tüketimini Ve Toplam Teslim Gecikme Süresini Minimize Etmek İçin Enerji Odaklı Çizelgeleme Optimizasyonu

Abstract

Günümüzde küresel ısınma, yasal zorunluluklar ve şirket giderlerinin düşürülmesi gibi birçok nedenden dolayı enerji yoğun üretim sistemleri için enerji tüketimini azaltmak önemli bir hedef haline gelmiştir. Bu nedenle, bu makalede üretim sistemlerinde enerji odaklı çizelgeleme problemine odaklanılmıştır. Sıra bağımlı hazırlık süreli (SBHS) tek makineli bir üretim sisteminde farklı geliş zamanlarına sahip işlerin toplam enerji tüketimini ve toplam teslim gecikme süresini minimize etmeyi sağlayan bir karma tamsayılı doğrusal olmayan programlama (MINLP) modeli geliştirilmiştir. Problemi çözmek için sezgisel bir yöntem olan genetik algoritma (GA) tabanlı enerji odaklı genetik optimizasyon (EGOP) yöntemi önerilmiştir. Önerilen yöntemin performansını değerlendirmek için amaç değerleri ve hesaplama süreleri analitik çözüm ve General Algebraic Modeling System (GAMS) çözüm ile karşılaştırılmıştır. Sonuç olarak, önerilen EGOP yönteminin etkili sonuçlar verdiği görülmüştür.

Keywords

Enerji tüketimi, genetik algoritma, iş çizelgeleme, sıra bağımlı hazırlık süresi.

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