求解多准则:总完工时间、总迟到时间和最大提前时间问题

Q1 Engineering
Nagham Muosa Neamah, B. A. Kalaf
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引用次数: 0

摘要

在本研究中,以最小化多准则和多目标函数为研究对象,研究了单机作业调度问题。第一个问题是最小化包含总完成时间、总迟到时间和最大提前时间的多准则(∑𝑗,∑𝑗,𝑚𝑎分),第二个问题是最小化多目标函数∑𝑗+∑𝑗+ 𝑚𝑎分)。在本研究中,建立了一个数学模型来解决研究问题,一些规则为这些问题提供了有效(最优)的解决方案。同时也证明了∑𝑗+∑∑𝑗+ 𝑚𝑎显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性显性。由于这些问题是NP-hard问题,因此很难确定这些问题的有效(最优)解集,因此给出了一些特殊的例子,并证明了这些例子可以找到适合所讨论问题的有效(最优)解,并强调了优势规则(DR)的意义,该规则可以应用于该问题以增强有效解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Solving the multi-criteria: Total completion time, total late work, and maximum earliness problem
Within this research, The problem of scheduling jobs on a single machine is the subject of study to minimize the multi-criteria and multi-objective functions. The first problem, minimizing the multi-criteria, which include Total Completion Time, Total Late Work, and Maximum Earliness Time (∑𝐶 𝑗 , ∑𝑉 𝑗 , 𝐸 𝑚𝑎𝑥 ) , and the second problem, minimizing the multi-objective functions ∑𝐶 𝑗 + ∑𝑉 𝑗 + 𝐸 𝑚𝑎𝑥 are the problems at hand in this paper. In this study, a mathematical model is created to address the research problems, and some rules provide efficient (optimal) solutions to these problems. It has also been proven that each optimal solution for ∑𝐶 𝑗 + ∑𝑉 𝑗 + 𝐸 𝑚𝑎𝑥 is an efficient solution to the problem (∑𝐶 𝑗 , ∑𝑉 𝑗 , 𝐸 𝑚𝑎𝑥 ) . Because these problems are NP-hard problems so it is difficult to determine the efficient (optimal) solution set for these problems so some special cases are shown and proven which find some efficient (optimal) solutions suitable for the discussed problem, and highlight the significance of the Dominance Rule (DR), which can be applied to this problem to enhance efficient solutions.
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来源期刊
CiteScore
1.90
自引率
0.00%
发文量
140
审稿时长
7 weeks
期刊介绍: *Industrial Engineering: 1 . Ergonomics 2 . Manufacturing 3 . TQM/quality engineering, reliability/maintenance engineering 4 . Production Planning 5 . Facility location, layout, design, materials handling 6 . Education, case studies 7 . Inventory, logistics, transportation, supply chain management 8 . Management 9 . Project/operations management, scheduling 10 . Information systems for production and management 11 . Innovation, knowledge management, organizational learning *Mechanical Engineering: 1 . Energy 2 . Machine Design 3 . Engineering Materials 4 . Manufacturing 5 . Mechatronics & Robotics 6 . Transportation 7 . Fluid Mechanics 8 . Optical Engineering 9 . Nanotechnology 10 . Maintenance & Safety *Computer Science: 1 . Computational Intelligence 2 . Computer Graphics 3 . Data Mining 4 . Human-Centered Computing 5 . Internet and Web Computing 6 . Mobile and Cloud computing 7 . Software Engineering 8 . Online Social Networks *Electrical and electronics engineering 1 . Sensor, automation and instrumentation technology 2 . Telecommunications 3 . Power systems 4 . Electronics 5 . Nanotechnology *Architecture: 1 . Advanced digital applications in architecture practice and computation within Generative processes of design 2 . Computer science, biology and ecology connected with structural engineering 3 . Technology and sustainability in architecture *Bioengineering: 1 . Medical Sciences 2 . Biological and Biomedical Sciences 3 . Agriculture and Life Sciences 4 . Biology and neuroscience 5 . Biological Sciences (Botany, Forestry, Cell Biology, Marine Biology, Zoology) [...]
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