Facility Layout Optimization: Bridging Theory and Practice

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".

Deadline for manuscript submissions: closed (31 January 2025) | Viewed by 1205

Special Issue Editor


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Guest Editor
Faculty of Computer Science and Management, Wrocław University of Science and Technology, 50-370 Wrocław, Poland
Interests: facility layout optimization (in production and logistics management, interface and ergonomic design); human–computer interaction (HCI) (usability of software and websites, interface design (studies involving eye tracking and face reading)); marketing (e-business, graphic information conveyance, digital signage (studies involving eye tracking and face reading)); ergonomics and human factors (digital human modeling (anthropometry), workload assessment); project management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue seeks to bridge the gap between theoretical advancements and practical applications in the realm of facility layout optimization. The primary aim is to facilitate a nuanced understanding of the interplay between theoretical frameworks and their real-world applications, aiming to propel the field forward. By combining theoretical rigor with practical insights, the goal is to significantly contribute to the development of more adaptive, effective, efficient, and sustainable facility layouts. This Special Issue aims to serve as a catalyst for discussions that not only advance the theoretical foundations but also address the practical challenges encountered in implementing facility layout optimization strategies across diverse industries.

The scope of this Special Issue encompasses a broad spectrum of topics to create a holistic perspective on facility layout optimization. We invite contributions covering, but not limited to, the following key aspects:

  • Algorithmic Advancements and Theoretical Foundations: Presenting novel algorithms and optimization methodologies while fostering a deeper understanding of the underlying theoretical frameworks that drive facility layout optimization.
  • Practical Applications and Case Studies: Showcasing successful real-world applications of facility layout optimization across various industries, providing insights into challenges faced and innovative solutions implemented.
  • Interdisciplinary Approaches: Encouraging contributions that bridge disciplines, such as operations research, industrial engineering, and computer science, to foster collaborative solutions that address the complexity of facility layout optimization.
  • Integration of Emerging Technologies: Exploring the incorporation of emerging technologies like artificial intelligence, machine learning, and Industry 4.0/5.0 into facility layout optimization algorithms for increased adaptability, effectiveness, and efficiency.
  • Sustainability Considerations: Investigating how facility layout optimization algorithms can contribute to sustainable practices, encompassing aspects such as energy efficiency, waste reduction, and environmental impact.

Dr. Rafał Michalski
Guest Editor

Manuscript Submission Information

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Keywords

  • facility layout optimization
  • algorithmic advancements
  • theoretical foundations
  • practical applications
  • case studies
  • interdisciplinary approaches
  • emerging technologies
  • artificial intelligence
  • machine learning
  • Industry 4.0
  • Industry 5.0
  • sustainability
  • energy efficiency
  • waste reduction
  • environmental impact
  • operational excellence

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Published Papers (1 paper)

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Research

19 pages, 1851 KiB  
Article
Nonlinear Optimization and Adaptive Heuristics for Solving Irregular Object Packing Problems
by János D. Pintér, Ignacio Castillo and Frank J. Kampas
Algorithms 2024, 17(11), 480; https://doi.org/10.3390/a17110480 - 25 Oct 2024
Viewed by 746
Abstract
We review and present several challenging model classes arising in the context of finding optimized object packings (OP). Except for the smallest and/or simplest general OP model instances, it is not possible to find their exact (closed-form) solution. Most OP problem instances become [...] Read more.
We review and present several challenging model classes arising in the context of finding optimized object packings (OP). Except for the smallest and/or simplest general OP model instances, it is not possible to find their exact (closed-form) solution. Most OP problem instances become increasingly difficult to handle even numerically, as the number of packed objects increases. Specifically, here we consider classes of general OP problems that can be formulated in the framework of nonlinear optimization. Research experience demonstrates that—in addition to utilizing general-purpose nonlinear optimization solver engines—the insightful exploitation of problem-specific heuristics can improve the quality of numerical solutions. We discuss scalable OP problem classes aimed at packing general circles, spheres, ellipses, and ovals, with numerical (conjectured) solutions of non-trivial model instances. In addition to their practical relevance, these models and their various extensions can also serve as constrained global optimization test challenges. Full article
(This article belongs to the Special Issue Facility Layout Optimization: Bridging Theory and Practice)
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