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Aiming at the problem that the number of spatial object catalogs is not high and the scheduling efficiency is low in traditional scheduling methods, a scheduling method using multi-rule scheduling strategy is proposed to maximize the number of object catalogs. This paper takes observation requirements and tracking arcs as inputs, forecasts the visibility of space target tracking arcs, integrates a variety of scheduling rules into the traditional scheduling process, and compares the scheduling results under two different scheduling strategies through simulation experiments with the number of multiple groups of different space targets as references. Experiments show that the same 5 monitoring devices perform the task of cataloging space objects. When the utilization rate of monitoring resources is close to 100%, the scheduling strategy based on multi-rules can achieve a maximum of 6 500 space objects stable cataloging, while the traditional scheduling strategy can only achieve a maximum of 3 200 space objects stable cataloging. Compared with the traditional scheduling strategy, the maximum number of catalogs is increased by 103%.

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This paper presents optimization of makespan for Flexible Job Shop Scheduling Problems (FJSSP) using an Improved Genetic Algorithm integrated with Rules (IGAR). Machine assignment is done by Genetic Algorithm (GA) and operation selection is done using priority rules. Improvements in GA include a new technique of adaptive probabilities and a new forced mutation technique that positively ensures the generation of new chromosome. The scheduling part also proposed an improved scheduling rule in addition to four standard rules. The algorithm is tested against two well-known benchmark data set and results are compared with various algorithms. Comparison shows that IGAR finds known global optima in most of the cases and produces improved results as compared to other algorithms.

This paper focuses on essential aspects of production scheduling in a specific job shop environment, with the primary objective of optimizing operational efficiency. Through a detailed simulation conducted in the Lekin application, a Job Shop Scheduling (JSS) system developed by M. Pinedo, we introduced four distinct jobs, each characterized by specific parameters, such as processing times at machines and due dates. We explore various scheduling rules, including Earliest Due-Date (EDD), Longest Processing Time (LPT), Shortest Processing Time (SPT), First Come First Serve (FCFS), Critical Ratio (CR), and Minimum Slack (MS), assessing their impact on system efficiency and performance. Each job, with its unique requirements and constraints, adds complexity to the production process, and our goal is to identify optimal strategies for managing these challenges in a dynamic and complex environment. The detailed analysis of simulation results and the comparison between different scheduling rules will contribute to the development of efficient methodologies for optimizing production scheduling in a diverse and constantly changing context. The outcomes of this paper have the potential to make significant contributions to enhancing the performance of production scheduling systems, addressing the specific requirements of contemporary industries.

Power generation dispatching is a large complex system problem with multi-dimensional and nonlinear characteristics. A mathematical model was established based on the principle of reservoir operation. A large quantity of optimal scheduling processes were obtained by calculating the daily runoff process within three typical years, and a large number of simulated daily runoff processes were obtained using the progressive optimality algorithm (POA) in combination with the genetic algorithm (GA). After analyzing the optimal scheduling processes, the corresponding scheduling rules were determined, and the practical formulas were obtained. These rules can make full use of the rolling runoff forecast and carry out the rolling scheduling. Compared with the optimized results, the maximum relative difference of the annual power generation obtained by the scheduling rules is no more than 1%. The effectiveness and practical applicability of the scheduling rules are demonstrated by a case study. This study provides a new perspective for formulating the rules of power generation dispatching.

An adequate bowel preparation for colonoscopy is best achieved by giving the cleansing regimen as a split-dose with the second dose given 4-6 hours before the procedure. This can be difficult to administer to diabetics who are preferentially scheduled for early morning procedures. We examined the impact on bowel preparation quality of scheduling diabetics for mid-morning (9:30 am or later) procedures rather than early morning procedures (7:30-9:00 AM) to facilitate a split-dose preparation.Historical cohort study of 34,415 patients (1,805 diabetics) age 18-74 years without significant comorbidities who underwent an outpatient colorectal cancer screening-related colonoscopy either before (2013) or after (2014) a unit wide change in scheduling practices for diabetics. The primary outcome was the rate of inadequate bowel preparation. Secondary outcomes include the rate of procedures complete to the cecum, procedure duration and detection rates of polyps, any colorectal cancer screening-relevant lesion (adenoma, sessile serrated adenoma, large proximal hyperplastic polyp) and advanced adenomas.From 2013 to 2014, the proportion of diabetics with an inadequate bowel preparation decreased from 7.7% to 3.2% (95% confidence interval for the difference 2.2%-6.8%, P

This paper focuses on essential aspects of production scheduling in a specific job shop environment, with the primary objective of optimizing operational efficiency. Through a detailed simulation conducted in the Lekin application, a Job Shop Scheduling (JSS) system developed by M. Pinedo, we introduced four distinct jobs, each characterized by specific parameters, such as processing times at machines and due dates. We explore various scheduling rules, including Earliest Due-Date (EDD), Longest Processing Time (LPT), Shortest Processing Time (SPT), First Come First Serve (FCFS), Critical Ratio (CR), and Minimum Slack (MS), assessing their impact on system efficiency and performance. Each job, with its unique requirements and constraints, adds complexity to the production process, and our goal is to identify optimal strategies for managing these challenges in a dynamic and complex environment. The detailed analysis of simulation results and the comparison between different scheduling rules will contribute to the development of efficient methodologies for optimizing production scheduling in a diverse and constantly changing context. The outcomes of this paper have the potential to make significant contributions to enhancing the performance of production scheduling systems, addressing the specific requirements of contemporary industries.

Consider the dispatch problem for a wafer fabrication where production process is divided into hundreds of operations and takes a few months to complete. In the process, wafers have to go through similar operations several times repeatedly for different layers of circuit, called job re-entrances. General family-based scheduling rules are proved to perform better than the individual job scheduling rule in terms of machine utilization for multiserver and multiple job re-entrance manufacturing systems under the condition that with a positive possibility, a queue exists in front of steppers. Five special family-based scheduling rules are constructed, of which FCFS-F, SRPT-F, EDD-F, and LS-F are modified from previous well-known scheduling rules, while SDA-F is a rule-based algorithm, using threshold control and least slack principles and being developed in this research. A simulation model is built to evaluate the performances of these five family-based rules by using the information collected from a wafer fab located in Hsin-Chu, Taiwan. As a result, SDA-F is shown to perform best among all five rules, followed by LS-F and FCFS-F. Index Terms--Dispatching rule, family-based scheduling, sequence-dependent manufacturing, wafer fabrication.

Just-In-Time (JIT) production systems capitalize on simplicity and the ability of workers to make decisions in a decentralized manner. In a multiproduct line operating under kanban control, the production worker at a given station must schedule the different jobs awaiting processing using information available locally. In practice, the first-come-first-served (FCFS) rule is commonly used. Recent results reported in the literature indicated that the shortest-processing-time (SPT) rule performed better than the FCFS rule. In this paper, we provide a simulation evaluation of the performance of a number of scheduling rules operating under different JIT production scenarios. Our hypothesis is that there are differences in the relative performance of the scheduling rules under different production scenarios. We differentiate among the JIT scenarios by the extent of setup time reduction already carried out (as indicated by the ratio of setup to processing times), the amount of slack in the system (as measured by the number of kanbans circulating), the extent to which uncertainty has been eliminated (as determined by the stochasticity of processing times), and the complexity of production requirements (as specified by the product-mix in mixed-model assembly). In this way, this paper provides further insights into the performance of scheduling rules operating under different JIT production environments, thereby adding to the scope and depth of research in this particular aspect of JIT production systems. Key words - Just-In-Time, scheduling, simulation

The paper deals with the classical problem of minimizing the makespan in a two-machine flow shop. When the job processing times are deterministic, the optimal job sequence can be determined by applying Johnson's rule. When they are independent and exponential random variables. Talwar's rule yields a job sequence that minimizes the makespan stochastically. Assuming that the random job processing times are independent and Gompertz distributed, we propose a new scheduling rule that is a generalization of both Johnson's and Talwar's rules. We prove that our rule yields a job sequence that minimizes the makespan stochastically. Extensions to m-machine proportionate stochastic flow shops, two-machine stochastic job shops, and stochastic assembly systems are indicated. Keywords: Gompertz distribution; Johnson's rule; makespan; scheduling; stochastic flow shop; Talwar's rule

Results of a research aimed at evaluating due date, resource allocation, project release, and activity scheduling rules in a multiproject environment indicated that workload sensitive due date rules offer improved due date estimates than workload insensitive due date rules. The performance of due date sensitive resource allocation rules is highly influenced by due date nervousness. The due date insensitive First In Project release rules can function better that the due date sensitive resource allocation rules when due date nervousness is not lessened.