Academic Journal
Smart and sustainable flow-shop scheduling problems: Scenario-based robust optimization and strong heuristics
| العنوان: | Smart and sustainable flow-shop scheduling problems: Scenario-based robust optimization and strong heuristics |
|---|---|
| المؤلفون: | Fathollahi-Fard, Amir M. |
| بيانات النشر: | École de technologie supérieure |
| سنة النشر: | 2023 |
| المجموعة: | École de technologie supérieure, Montréal: Espace ÉTS |
| مصطلحات موضوعية: | production intelligente, production durable, ateliers de permutation distribués, métaheuristiques |
| الوصف: | This Ph.D. thesis is dedicated to the development of a smart and sustainable approach to the Distributed Permutation Flow Shop Scheduling Problem (DPFSP) through the utilization of practical optimization models, efficient reformulations, heuristics, and advanced metaheuristics. The DPFSP is an extension of the Permutation Flow Shop Scheduling Problem (PFSP) and serves as its foundational model. The key distinction between the DPFSP and the PFSP lies in their respective scheduling scopes. While the PFSP focuses on scheduling tasks within a single plant, the DPFSP addresses the more complex challenge of scheduling tasks across multiple distributed factories. While prior research has made contributions to the field of DPFSP, this Ph.D. project stands out by incorporating the concepts of sustainability, real-time scheduling, and scenario-based robust optimization into the DPFSP framework. The primary objective of this research is to integrate environmental and social criteria based on the Triple Bottom Line (TBL) to meet the guidelines of the Sustainable Development Goals (SDGs). By considering criteria such as energy consumption, job opportunities, and lost workdays, a multi-objective optimization model and an efficient multi-objective metaheuristic algorithm are developed. Another critical research gap in the field of production scheduling involves the intelligent collection, analysis, and conversion of data into actionable information using real-time decision-making strategies for production systems. In response to this grand challenge, the second objective of this Ph.D. project is to address the uncertainty in the DPFSP by modeling it within the real-time optimization framework of Industry 4.0. A real-time optimization approach is proposed to handle task reassignment to machines under uncertain process times, new task arrivals, or planned machine breakdowns. By incorporating the concepts of Industry 4.0, a comprehensive optimization model using different manual and automated modes of production is proposed and ... |
| نوع الوثيقة: | article in journal/newspaper thesis |
| وصف الملف: | application/pdf |
| اللغة: | English |
| Relation: | https://espace.etsmtl.ca/id/eprint/3361/1/FATHOLLAHIFARD_AmirMohammad.pdf; Fathollahi-Fard, Amir M. (2023). Smart and sustainable flow-shop scheduling problems: Scenario-based robust optimization and strong heuristics. Thèse de doctorat électronique, Montréal, École de technologie supérieure. |
| الاتاحة: | https://espace.etsmtl.ca/id/eprint/3361/ https://espace.etsmtl.ca/id/eprint/3361/1/FATHOLLAHIFARD_AmirMohammad.pdf |
| رقم الانضمام: | edsbas.DAE9ADC8 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |