Search

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%. more...

Distributed processing and assembly multistage manufacturing system consist of multiple job shop for processing parts and a general assembly flow shop for partial and final assembly. Dynamic orders with multi-layer product structures require part matching before assembly. The control of such multistage shop involves joint decision-making on order allocation, processing, and assembly jobs scheduling for precise coordination between the two levels of production. An automatic design method of scheduling rules for distributed machining and assembly multistage workshops based on genetic programming based on parallel simulation(GP-PS) was proposed. Firstly, a mathematical model was established to minimize the percentage of tardy product. Then, an improved genetic programming algorithm was introduced to integrate evolutionary multistage scheduling rules. A population optimization mechanism was designed to prevent the algorithm from converging locally, while parallel simulation technology was embedded to effectively reduce training time. Finally, simulation experiments were conducted to validate the performance of the improved genetic algorithm. The experimental results show that the percentage of tardy product obtained from the manual rule set, standard genetic programming, and improved algorithm is respectively 6. 44%, 5. 65% and 2. 67%. The improved GP algorithm based on parallel simulation optimization can achieve more obvious comprehensive performance advantages than dozens of preferred artificial rule groups and the optimal rule groups generated by standard GP algorithm. It is feasible and effective to use this algorithm to automatically design multi-level rules of integrated scheduling for DPAMW scheduling problem. [ABSTRACT FROM AUTHOR] more...

Copyright of Command Control & Simulation / Zhihui Kongzhi yu Fangzhen is the property of Command Control & Simulation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) more...

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. more...

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. more...

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. more...