Recent Algorithms for Operation Research in Logistics, Project Planning and Scheduling

Dear Colleagues,

The aim of this Special Issue is to gather the latest research on the development and application of novel algorithms for operation research (OR) in logistics, project planning, and scheduling.

The recent developments in information and communication technologies, such as big data, cloud computing, artificial intelligence, and the Internet of Things, have enabled the emergence of Industry 4.0 and Industry 5.0, which are characterized by the integration of physical and cyber systems, human–machine collaboration, and the customization and personalization of products and services. These developments have also brought new challenges and opportunities for OR, such as the need to handle large-scale, high-dimensional, and heterogeneous data, the need to incorporate human factors and preferences, and the need to cope with rapidly changing and unpredictable situations.

The COVID-19 pandemic has also posed unprecedented challenges for OR, such as the disruption of global supply chains, the increased demand for healthcare and emergency services, the shift to online and remote work and education, and the social and economic impacts of lockdowns and restrictions. These challenges have highlighted the importance of OR in providing effective solutions for crisis management, resilience, and recovery.

We invite original and high-quality submissions that present novel algorithms and methods for OR in logistics, project planning, and scheduling, with a focus on addressing the new challenges and opportunities arising from the pandemic, and challenges in Industry 4.0 and Industry 5.0. We welcome submissions that present new theoretical, computational, or empirical contributions to the field of algorithms, as well as case studies and applications that demonstrate the practical impact and value of novel algorithms in real-world problems.

Topics of interest include, but are not limited to, the following:

• Data-driven and machine learning-based algorithms for supply chains;
• Multi-objective and multi-criteria optimization algorithms for project planning and scheduling;
• Stochastic, robust, and adaptive optimization algorithms for logistics, project planning, and scheduling;
• Meta-heuristics and hybrid algorithms for scheduling;
• Distributed and parallel algorithms for logistics and project planning;
• Simulation and scenario analysis algorithms for supply chains;
• Decision support systems and tools based on algorithms for project and supply chain management;
• Novel algorithms for scheduling, project planning, resource allocations, logistics, and supply chain management;
• Novel algorithms for transportation and mobility, smart manufacturing and services, and for Industry 4.0 and Industry 5.0.

Prof. Dr. Zsolt Tibor Kosztyán
Guest Editor

Manuscript Submission Information

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