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Introduction of digital solutions has made dentistry more efficient and effective in response to patients' demands. Moreover, digital solution helps participants to manage daily workflow simpler than traditional practices. Scanners, CAD/CAM software, CNC machines and 3D printers are components of digital solutions in current dentistry. Responding to patients as quickly as possible is essential in medical fields and dentistry has similar situations. On the other hand, demands in dentistry are highly customized that it makes managing orders more difficult because each order needs special design and production. Thus, this paper assesses orders in digital dentistry and develops a mathematical model to optimize production planning and scheduling of orders by considering different objectives and requirements that are common in dentistry. In addition, a metaheuristics algorithm was developed based on PSO to respond to NP-hard challenges of the model. The developed algorithm includes two steps that PSO metaheuristics consider in the second step to search new solutions. Finally, through case studies, performance of the developed model and proposed algorithm was investigated. Developed algorithm generates solutions with proper quality considering makespan and total completion time objectives and required time to obtain a solution with high quality depends on problem data and can increase. [ABSTRACT FROM AUTHOR]

This paper introduces a new variant of the Bees Algorithm (BA) called Bees Algorithm with 2-parameter (BA2), which is a population-based metaheuristic algorithm designed to solve continuous and combinatorial optimisation problems. The proposed algorithm simplified the BA's parameters by combining exploration and exploitation strategies while preserving the algorithm's core principles to efficiently search for optimal solutions. The paper provides a detailed description of the algorithm's core principles and its application to two engineering problems, the air-cooling system design (ACSD) and the printed circuit board assembly sequence optimisation (PASO). The results show that BA2 outperforms previous versions of the basic BA in terms of convergence speed and solution quality. However, the authors acknowledge that further research is needed to test the scalability and generalisability of the algorithm to larger and more diverse optimisation problems. Overall, this paper provides valuable insights into the potential of metaheuristics for solving real-world optimisation problems. [ABSTRACT FROM AUTHOR]

This paper considers the no-wait job shop (NWJS) problem with makespan minimisation criteria. It is well known that this problem is strongly NP-hard. Most of the previous studies decompose the problem into a timetabling sub-problem and a sequencing sub-problem. Each study proposes a different sequencing and timetabling algorithm to solve the problem. In this research, this important question is aimed to be answered: is the timetabling or the sequencing algorithm more important to the effectiveness of the developed algorithm? In order to find the answer, three different sequencing algorithms are developed; a tabu search (TS), a hybrid of tabu search with variable neighbourhood search (TSVNS), and a hybrid of tabu search with particle swarm optimisation (TSPSO). Afterwards, the sequencing algorithms are combined with four different timetabling methods. All the approaches are applied to a large number of test problems available in the literature. Statistical analysis reveals that although some of the sequencing and timetabling algorithms are more complicated than the others, they are not necessarily superior to simpler algorithms. In fact, some of the simpler algorithms prove to be more effective than complicated and time-consuming methods. [ABSTRACT FROM PUBLISHER]

It has been nearly two decades since the last major review of the literature in dynamic facility layout. In these intervening years, many advances have been made in modelling as well as in the solution methods. In this study, models and solutions that address the dynamic facility layout problem (DFLP) are examined and categorized. Our review finds that the recent DFLP models consider more complex design features and constraints. Further, only a few DFLP studies have adopted exact methods, while most of the effective algorithms used are heuristics, metaheuristics and hybrid approaches. Future research directions are also identified. [ABSTRACT FROM AUTHOR]