operations research

简明释义

管理研究

英英释义

例句

1.The company applied operations research to optimize its supply chain management.

公司应用运筹学来优化其供应链管理。

2.The logistics firm employed operations research to minimize delivery times.

物流公司采用运筹学来最小化交货时间。

3.By utilizing operations research, the airline improved its flight scheduling efficiency.

通过利用运筹学，航空公司提高了航班调度的效率。

4.In healthcare, operations research helps in resource allocation and patient flow management.

在医疗保健中，运筹学有助于资源分配和患者流动管理。

5.The team used operations research methods to analyze customer behavior patterns.

团队使用运筹学方法分析客户行为模式。

作文

In today's fast-paced world, organizations are constantly seeking ways to improve their efficiency and effectiveness. One of the most valuable tools available for achieving this goal is operations research. 运筹学 is a discipline that applies advanced analytical methods to help make better decisions. It combines various techniques from mathematics, statistics, and computer science to analyze complex systems and optimize performance.The origins of operations research can be traced back to World War II when it was used to improve military logistics and operations. Since then, its application has expanded to various fields, including business, healthcare, transportation, and manufacturing. Organizations utilize operations research to solve problems related to resource allocation, scheduling, inventory management, and supply chain optimization.One of the key components of operations research is mathematical modeling. This involves creating abstract representations of real-world systems to analyze their behavior and predict outcomes under different scenarios. For instance, in a manufacturing setting, a company might use operations research to model the production process, identify bottlenecks, and determine the optimal number of workers needed to meet demand without incurring excess costs.Another important aspect of operations research is optimization. This refers to the process of finding the best solution from a set of feasible options. Optimization techniques, such as linear programming and integer programming, are commonly employed to maximize or minimize objective functions while satisfying constraints. For example, a logistics company might use operations research to minimize transportation costs while ensuring timely delivery of goods.In addition to optimization, operations research also encompasses simulation. Simulation allows organizations to model complex systems and assess how they would perform under various conditions. By running simulations, decision-makers can gain insights into potential risks and uncertainties, enabling them to make informed choices. For instance, a healthcare provider may use simulation techniques to evaluate patient flow in an emergency department and identify ways to reduce waiting times.The impact of operations research on decision-making is profound. By leveraging data and analytical techniques, organizations can make evidence-based decisions that lead to improved outcomes. For example, retailers can use operations research to optimize their inventory levels, ensuring that they have the right products available at the right time, which ultimately enhances customer satisfaction.Furthermore, the integration of technology in operations research has revolutionized the field. With the advent of big data and advanced analytics, organizations can now analyze vast amounts of information to uncover patterns and trends that were previously hidden. This ability to harness data allows for more accurate predictions and better-informed strategic planning.In conclusion, operations research is an essential discipline that provides organizations with the tools needed to tackle complex problems and enhance decision-making. Its applications span a wide range of industries, making it a versatile approach to improving efficiency and effectiveness. As organizations continue to face increasing competition and complexity, the importance of operations research will only grow, enabling them to navigate challenges and seize opportunities in an ever-changing landscape.

在当今快节奏的世界中，组织不断寻求提高效率和效果的方法。可用于实现这一目标的最有价值的工具之一是运筹学。运筹学是一门应用先进分析方法以帮助做出更好决策的学科。它结合了数学、统计学和计算机科学的各种技术，以分析复杂系统并优化性能。运筹学的起源可以追溯到第二次世界大战，当时它被用来改善军事后勤和操作。从那时起，它的应用扩展到了各个领域，包括商业、医疗保健、交通运输和制造业。组织利用运筹学来解决与资源分配、调度、库存管理和供应链优化相关的问题。运筹学的一个关键组成部分是数学建模。这涉及创建现实世界系统的抽象表示，以分析其行为并预测在不同场景下的结果。例如，在制造环境中，一家公司可能会使用运筹学来建模生产过程，识别瓶颈，并确定满足需求而不产生过多成本所需的最佳工人人数。运筹学的另一个重要方面是优化。这是指在一组可行选项中找到最佳解决方案的过程。优化技术，如线性规划和整数规划，通常用于最大化或最小化目标函数，同时满足约束条件。例如，一家物流公司可能会使用运筹学来最小化运输成本，同时确保货物的及时交付。除了优化之外，运筹学还包括模拟。模拟允许组织模型复杂系统并评估在各种条件下的表现。通过运行模拟，决策者可以获得潜在风险和不确定性的见解，使他们能够做出明智的选择。例如，医疗保健提供者可能会使用模拟技术来评估急诊部门的病人流量，并确定减少等待时间的方法。运筹学对决策的影响深远。通过利用数据和分析技术，组织可以做出基于证据的决策，从而改善结果。例如，零售商可以使用运筹学来优化库存水平，确保在正确的时间拥有正确的产品，从而最终提高客户满意度。此外，技术在运筹学中的整合彻底改变了这一领域。随着大数据和高级分析的出现，组织现在可以分析大量信息，以揭示先前隐藏的模式和趋势。这种利用数据的能力使得更准确的预测和更好的战略规划成为可能。总之，运筹学是一门必不可少的学科，为组织提供了解决复杂问题和增强决策能力所需的工具。它的应用涵盖广泛的行业，使其成为改善效率和效果的多功能方法。随着组织面临越来越激烈的竞争和复杂性，运筹学的重要性只会增加，使它们能够在不断变化的环境中应对挑战和把握机遇。