_applied sciences_  
_Editorial_  
Planning and Scheduling Optimization  
[PERSON] \({}^{1,2,\star}\)\({}^{\copyright}\), [PERSON] \({}^{1}\) and [PERSON] \({}^{1,2}\)  
\({}^{1}\) Laboratoire Informatique et Soeite Numerique, Universite de Technologie de Troyes, 12 rue Marie Curie, CS 42060, 10004 Troyes, France; [EMAIL_ADDRESS] (T.A. ); [EMAIL_ADDRESS] (F.Y)  
\({}^{2}\) Chaire Connected Innovation, Universite de Technologie de Troyes, 12 rue Marie Curie, CS 42060, 10004 Troyes, France  
\({}^{\star}\) Correspondence: [EMAIL_ADDRESS]  
Optimizing the performance of services and industrial systems is a real lever for creating value for companies and society. However, this target requires significant research efforts. This optimization phase is one of the major steps that make it possible to guarantee optimized productivity while respecting numerous constraints, such as quality standards, safety of manufacturing processes, environmental impact and other economic constraints. These constraints are linked to the type of products, the type of manufacturing systems and their environment. In most industries, the main objective is to guarantee an optimized use of workshops, plants and other logistics resources in order to be reactive to market changes and disturbances. From this perspective, industrial systems must be as flexible as possible in order to be able to adapt in terms of resources allocation, workshop reorganization, capacities allocation, etc. This special issue is devoted to recent research and current developments on complex systems' planning and scheduling. This includes the principles and practice of the design, implementation and analysis of exact and approximate optimization methods to tackle the challenges of modern manufacturing, engineering and healthcare systems. The topics of interest of this issue include:  
* Heuristic and metaheuristic algorithms for planning and scheduling problems in manufacturing, engineering and healthcare systems;
* Exact algorithms (brand and bounds, dynamic programming, etc.) for planning and scheduling problems;
* Planning and scheduling applications (timetabling, network routing, crew scheduling, production scheduling, resource-constrained project scheduling, etc. );
* Energy-efficient planning and scheduling problems;
* Intelligent optimization approaches for intelligent manufacturing systems;
* Artificial Intelligence and data analytics (manufacturing, services, healthcare, services and industries of the future, etc.). In response to the call for papers, thirty-nine papers were submitted to this special issue among which sixteen were accepted for publication. One of the accepted works presents a systematic review and future directions for smart manufacturing scheduling approaches [1]. In this review, several papers published recently are analyzed to understand the requirements considered when developing scheduling solutions for manufacturing systems. Considering healthcare problems, [PERSON] et al. [2] addresses the generation and development of a benchmark properly fitting different constraints of the Home Health Care (HHC) problem. Consequently, a generator is proposed dealing with all kinds of constraints, such as time window constraints, workload constraints, synchronization and precedence constraints. This generator allows researchers to validate and compare solving methods on a common dataset, regardless of confidentiality issues. The author validate their generator, firstly, by creating a common benchmark available for researchersand, secondly, by proposing a set of instances and a solving method based on an HHC problem found in the literature. In another work, [PERSON] et al. [3] study a real case of an optimization problem derived from a hospital supply chain. Their work focuses on developing operational decision support models and algorithms for the production process scheduling in a hospital catering. The addressed production system is represented as a flexible job shop system.