İki amaçlı esnek atölye tipi çizelgeleme probleminin tasarımı ve analizi: İnşaat ekipmanları imalatı sektöründe bir vaka çalışması

Bu çalışmada esnek atölye tipi üretim çizelgeleme probleminin kapasite kısıtları altında programlanması için karmaşık tamsayı doğrusal optimizasyon modelinin tasarlanması ve geliştirilmesi kesin çözüm algoritması kullanılarak sağlanmıştır. Modelleme yaklaşımı, gerçek vakalar üzerinden veri analizini sağlamak, üretim hatlarındaki üretim süresini en aza indirmek, toplam üretim maliyetlerini azaltmak ve matematiksel programlama probleminin önemli özelliklerini detaylı olarak ortaya koymak için tasarlanmıştır. Bu çalışmanın temel amacı, iki amaçlı çizelgeleme problemleri için ϵ-kısıt yöntemini kullanarak daha hızlı ve verimli çözüm setleri elde etmektir. Gerçek hayat verileri kullanılarak elde edilen Pareto çözüm setleri karar vericiler ile paylaşılmıştır. İki amaçlı çizelgeleme problemi için geliştirilen karmaşık tamsayı doğrusal optimizasyon modelinin çözüm aşamasında GAMS programlama dili kullanılmıştır ve şirketin üretim maliyetlerinde %16.6’lık bir iyileştirme gerçekleştirilmiştir.

Design and analysis of bi-objective flexible job shop scheduling problem: A case study in construction equipment manufacturing industry

This paper presents a design and development of mixed-integer linear optimization model for scheduling of flexible job-shop production problem under capacity constraints by using exact solution algorithm. Modelling approach is designed in order to introduce data analysis in real situations, minimize production time in production lines, reduce total production costs, and reveal important features of mathematical programming problem in detail. The main purpose of this study is to obtain faster and efficient Pareto solution sets for bi-objective problem by using ϵ-constraint method. Generated Pareto frontier using real life data is shared with decision makers. The GAMS programming language is used during the solution phase of a mixed-integer linear optimization model for bi-objective problem and production efficiency of the company is increased around 16.6% in terms of production cost.

Kaynakça

Kalite Derneği (TMME). “2016 Türkiye Müşteri Memnuniyeti Endeksi”. http://www.kalder.org/tmme (11/02/2018).

Johnson SM. “Optimal two and three stage production schedules with setup times included”. Naval Research Logistics Quarterly, 1(1), 61-8, 1954.

Van Wassenhove LN, Baker KR. “A bi-criterion approach to time/cost trade-offs in sequencing”. European Journal of Operational Research, 11(1), 48-54, 1982.

Brucker P, Schlie R. “Job-shop scheduling with multi-purpose machines”. Computing, 45(4), 369-375, 1990.

Yazdani M, Gholami M, Zandieh M, Mousakhani M. “A simulated annealing algorithm for flexible job-shop scheduling problem”. Journal of applied sciences, 9(4), 662-670, 2009.

Kacem I, Hammadi S, Borne P. “Approach by localization and multi-objective evolutionary optimization for flexible job-shop scheduling problems”. IEEE Transactions on Systems, Man and Cybernetics, 32(1), 1-13, 2002.

Paulli J. “A hierarchical approach for FMS scheduling problem”. European Journal of Operational Research, 86, 32-42, 1995.

Watanabe M, Ida K, Gen M. “A genetic algorithm with modified crossover operator and search area adaptation for the job-shop scheduling problem”. Computers & Industrial Engineering, 48(4), 743-752, 2005.

Fattahi P, Saidi M, Jolai F. “Mathematical modeling and heuristic approaches to flexible job shop scheduling problems”. Journal of Intelligent Manufacturing, 18, 331-342, 2007.

Gao J, Gen M, Sun L, Zhao X. “A Hybrid of genetic algorithm and bottleneck shifting for multi-objective flexible job shop scheduling problems”. Computers & Industrial Engineering, 53(1), 149-162, 2007.

Chiang TC, Lin HJ. “A simple and effective evolutionary algorithm for multi-objective flexible job shop scheduling”. International Journal of Production Economics, 141 (1), 87-98, 2012.

Li J, Pan Q, Xie S. “An effective shuffled frog-leaping algorithm for multi-objective flexible job shop scheduling problems”. Applied Mathematics and Computation, 218, 9353-9371, 2012.

Abdeljaouad MA, Bahroun Z, Omrane A, Fondrevelle J. “Job-shop production scheduling with reverse flows”. European Journal of Operational Research, 244(1), 117-128, 2015.

Gedik R, Rainwater C, Nachtmann H, Pohl EA. “Analysis of a parallel machine scheduling problem with sequence dependent setup times and job availability intervals”. European Journal of Operational Research, 251(2), 345-694, 2016.

Özgüven C, Yavuz Y, Özbakır L. “Mixed integer goal programming models for the flexible job-shop scheduling problems with separable and non-separable sequence dependent setup times”. Applied Mathematical Modelling, 36(2), 505-862, 2012.

Xue G, Offodile OF, Zhou H, Troutt MD. “Integrated production planning with sequence-dependent family setup times”. International Journal of Production Economics, 131(2), 674-681, 2011.

Shen L, Dauzère-Pérèsb S, Neufeldd JS. “Solving the flexible job shop scheduling problem with sequence-dependent setup times”. European Journal of Operational Research, 265, 399-794, 2017.

Gao KZ, Suganthan PN, Pan QK, Chua TJ, Cai TX, Chong CS. “Discrete harmony search algorithm for flexible job shop scheduling problem with multiple objectives”. Journal of Intelligent Manufacturing, 27(2), 1-12, 2014.

Mavrotas G. “Effective implementation of the e-constraint method in multi-objective mathematical programming problems”. Applied Mathematics and Computation, 213, 455-465, 2009.

Resat HG, Turkay M. “A discrete-continuous optimization approach for the design and operation of synchromodal transportation networks”. Computer and Industrial Engineering, 130, 512-525, 2019.