Guest Editors
Prof. Dr. Frank Werner, Otto-Von-Guericke-University, Germany
Dr. Mohammad Shokouhifar, Shahid Beheshti University, Iran
Summary
In the ever-evolving landscape of industrial and service operations, the ability to efficiently plan and schedule resources is critical for simultaneously achieving an optimal performance and competitiveness. Planning and scheduling problems are common in many industries such as production planning, supply chain management, logistics, healthcare and medical services, project planning, and smart cities. These problems are inherently complex, often involving multiple objectives with numerous constraints that need to be optimized. Therefore, developing robust algorithms is essential to effectively address these challenges and enable the efficient organization of resources, leading to optimal or near-optimal solutions.
This special issue aims to address the increasing complexity of planning and scheduling problems by exploring a wide range of algorithmic techniques and methodologies. Beyond exact and mathematical techniques, we also encourage contributions focusing on heuristics, hyperheuristics, and metaheuristics, fuzzy systems, and machine learning techniques that offer flexible and effective solutions. Furthermore, we are interested in the intelligent design of hybrid approaches that combine various algorithmic strategies to exploit their complementary strengths. Topics of interest include, but are not limited to:
Integer and mixed-integer programming
Nonlinear programming for complex system optimization
Stochastic programming for uncertain environments
Exact search techniques: branch and bound methods, dynamic programming, …
Heuristic, metaheuristic, and hyper-heuristic algorithms
Fuzzy sets and systems for uncertainty handling
Machine learning and reinforcement techniques
Hybrid heuristic-metaheuristic techniques
Hybrid metaheuristic-machine learning techniques
Hybrid learning-based hyperheuristic design algorithms
Just-in-time algorithms for dynamic scheduling
Applications in job-shop scheduling problems
Applications in resource allocation problems
Applications in project planning and scheduling
Applications in manufacturing and production planning
Applications in healthcare and medical services
Applications in IoT and smart cities
Keywords
Scheduling problems, Planning and control systems, Mathematical programming, Heuristics, metaheuristics, Fuzzy systems, Machine learning, Hybrid optimization algorithms
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