煤炭码头卸车调度问题多目标优化模型及算法

本文针对煤炭码头卸车调度问题,提出了相应的多约束多目标优化模型,并设计了采用仿真推演策略解码的遗传算法求解。首先,本文考虑列车、煤种、场存、设备、翻堆线和卸车作业过程等约束条件,以卸车效率最大和列车在港时间最短为目标,构建了煤炭码头卸车调度问题多目标数学模型。然后,综合运筹学、遗传算法以及仿真技术,给出了煤炭码头卸车调度问题遗传算法详细设计,包括组合式编码和仿真推演解码方法,染色体生成算法,适应度函数设计,以及采用多种策略的遗传操作及修正等,并列出了算法步骤。实例测试表明,本算法的执行效率高而且优化效果好,结果适用。     

中国运筹学：生机勃勃四十年

本文在简要回顾了近代运筹学的发展以及中国运筹学的发展历程之后,概述了中国运筹学四十年来的主要成果及其在国际运筹学界的地位。通过回顾近代运筹学的发展,指出了当代运筹学的特点和内涵。通过总结中国运筹学四十年来的主要成果,以便肯定成绩,认清差距,促进我国运...     

强化学习在运筹学的应用:研究进展与展望

强化学习已经成为人工智能领域一个新的研究热点,并已成功应用于各领域,强化学习将运筹优化领域的很多问题视为序贯决策问题,建模为马尔可夫决策过程并进行求解,在求解复杂、动态、随机运筹优化问题具有较大的优势。本文主要对强化学习在运筹优化领域的应用进行综述,首先介绍了强化学习的基本原理及其应用于运筹优化领域的研究框架,然后回顾并总结了强化学习在库存控制、路径优化、装箱配载和车间作业调度等方面的研究成果,并将最新的深度强化学习以及传统方法在运筹学领域的应用研究进行了对比分析,以突出深度强化学习的优越性。最后提出几个值得进一步探讨的研究方向,期望能为强化学习在运筹优化领域的研究提供参考。     

中国数学规划学科发展概述

数学规划又称数学优化, 是运筹学的一个重要分支. 它主要研究在一定约束条件下, 如何求一个实数或者整数变量的实函数的最大值或者最小值. 它是运筹学和管理科学中最常用的一种建模工具和求解问题的方法, 在工程、经济和金融等领域有非常广泛的应用. 首先简单介绍数学规划的发展历史、应用领域及其主要研究方向; 然后简述数学规划的发展现状和在中国的发展进程; 最后, 讨论数学规划若干研究前沿问题与研究展望.     

现代优化理论与应用

过去数十年间,现代运筹学,特别是优化理论、方法和应用有了长足的发展.本文就运筹与优化多个领域的一些背景知识、前沿进展和相关技术做了尽可能详尽的概述,涵盖了线性规划、非线性规划、在线优化、机器学习、组合优化、整数优化、机制设计、库存管理和收益管理等领域.本文的主要目标并非百科全书式的综述,而是着重介绍运筹学某些领域的主流方法、研究框架和前沿进展,特别强调了近期一些比较重要和有趣的发现,从而激发科研工作者在这些领域进行新的研究.     

《运筹与管理》2017年变更刊期及征订启事

<正>《运筹与管理》是中国运筹学会主办的学术性期刊。宗旨是交流运筹学与管理科学工作者的研究成果,推进运筹学在经济计划、投资决策、风险分析、企业管理、生产控制、结构优化、信息技术及军事领域的应用。主要刊登运筹学和管理科学方面的学术研究成果及在国     

《运筹与管理》2017年变更刊期及征订启事

<正>《运筹与管理》是中国运筹学会主办的学术性期刊。宗旨是交流运筹学与管理科学工作者的研究成果,推进运筹学在经济计划、投资决策、风险分析、企业管理、生产控制、结构优化、信息技术及军事领域的应用。主要刊登运筹学合管理科学方面的学术研究成果及在国     

中国运筹学发展研究报告

运筹学是自20世纪三四十年代发展起来的一门新兴交叉学科,主要研究如何应用数学和计算的理论与方法对社会系统和工程系统做出最优或满意的决策。为了更好地推动中国运筹学及相关领域的研究和应用,学会组织国内运筹学领域的部分专家,并参考了国内外运筹学多个分支代表性人物对运筹学的起源和发展的回忆与评述,共同完成了此报告。报告概述了运筹学的主要特征和方法,简述了运筹学的发展历程,剖析了运筹学研究中的成功经验,综述了运筹学几个主要分支的发展状况,介绍了运筹学中十几个有代表性的难题,展望了运筹学未来发展的方向。希望此报告能引起读者进一步思考运筹学的本质,运筹学是如何成长和将如何发展,并在一定程度上推动中国运筹学更好地发展。     

《运筹与管理》2017年变更刊期及征订启事

<正>《运筹与管理》是中国运筹学会主办的学术性期刊。宗旨是交流运筹学与管理科学工作者的研究成果,推进运筹学在经济计划、投资决策、风险分析、企业管理、生产控制、结构优化、信息技术及军事领域的应用。主要刊登运筹学和管理科学方面的学术研究成果及在国民经济各部门中创造性地解决实际问题行之有效的方法与经验。     

最优场址问题的研究进展

３０年代以来，最优场址问题一直是运筹学界阳活跃的研究领域之一。此问题具有深镔实验背景和广泛的实用价值。本文综述了最优场址问题研究进展并对其发展历史进行了简单的回顾，主要介绍近年来最优场址问题研究的一些重要成果，对每一种成果进行了基本的评论。     

1996~2017年《Operations Research》期刊发文统计分析

《Operations Research》(OR)是运筹与管理科学领域的顶级期刊,对其刊文进行统计分析,剖析国际运筹学科领域的主流研究机构及合作影响,探究当前研究热点问题及学科发展趋势,对于促进我国运筹学科领域的发展具有十分重要的指引作用.基于对WOS核心数据库中该期刊1996至2017年间全部刊文的统计分析,得出以下结论:近年来我国学者发文量稳步提升,表明我国运筹学科领域研究水平的显著提高,但其影响力仍有待进一步提升;机构合作、国际合作都有助于文章引文量的提升;引证分析显示柔性制造(流程柔性及效率)、巢式Logit模型的应用、网络收益管理等7个研究方向是当前、并继续成为运筹领域的研究热点.     

运筹学在整车物流智能调度决策支持系统中的研究与应用

本文基于整车物流智能调度决策支持系统的研发、实施与运维的成功应用,论述运筹学在智能化上的应用路径以及实践驱动的学术路径。该系统是国内较早在汽车物流企业实现落地的智能化调度系统,其所形成的思想理论与方法技术揭示了运筹学在智能化应用上的核心价值,以及实践驱动的学术价值,对解决“卡脖子”难题提供示范性思路。本文提出运筹学在智能化研发上“三环七步”的整体研发框架。首先,分析智能化需求的运筹学特征,详细介绍汽车整车物流的发展趋势、瓶颈及智能调度需求;其次,论述运筹学系统模型的作用与建模方法,分析汽车整车物流系统模型的决策要素、目标及约束,提出汽车整车物流智能调度的运筹学应用问题。然后,提出“模式装箱”的新装箱理论问题,明确问题的计算难解性、可解性及核心科学特征。进一步,建立汽车整车物流调度应用问题与科学问题的混合整数线性规划模型;提出求解汽车整车物流调度问题的分支定界算法,以及大规模问题求解的时空分解及滚动求解方法与技术;提出面向运筹应用的生产测试及压力测试方法,给出汽车整车物流调度的测试分析的流程与结果。此外,提出深度集成整车运输管理系统与仓库管理系统、优化算法引擎驱动的分布式、多视图、多系统融合的智能调度决策支持系统。最后,论述该系统在实施过程中的推广使用和运维情况,并对运筹学应用及实践驱动的科学研究进行总结与展望。     

A survey of berth allocation and quay crane scheduling problems in container terminals

Due to the variety of technical equipments and terminal layouts, research has produced a multitude of optimization models for seaside operations planning in container terminals. To provide a support in modeling problem characteristics and in suggesting applicable algorithms this paper reviews the relevant literature. For this purpose new classification schemes for berth allocation problems and quay crane scheduling problems are developed. Particular focus is put on integrated solution approaches which receive increasing importance for the terminal management.     

A Materialist Analysis of Operational Research

Accounts of the development and practice of operational research have commonly stressed its timeless universality as a method for rational decision-making. In this paper operational research is seen as one element in the managerial response to problems of complexity and uncertainty within an economic system characterised by institutionalised conflict. Both the material and ideological functions of ‘management science’ in private and public enterprise are analysed, and characteristics are identified of an emergent ‘workers science’. Editor's Note The title of this paper contrasts the materialistic approach with the idealistic approach, and the content of the paper disowns the latter. Evidently there are alternative but overtly political terms for both adjectives.It would be stupid if O.R. were to ignore the political facts of life which play so great a part in the decisions and policies with which O.R. is concerned. But, as the authors acknowledge, other interpretations of history than those presented here are at least possible.Contributions offering alternative schemata, or based on other paradigms, are invited and will be given careful consideration.     

A semi-oriented radial measure for measuring the efficiency of decision making units with negative data,using DEA

Data Envelopment Analysis (DEA) is a nonparametric method for measuring the efficiency of a set of decision making units such as firms or public sector agencies, first introduced into the operational research and management science literature by Charnes, Cooper, and Rhodes (CCR) [Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444]. The original DEA models were applicable only to technologies characterized by positive inputs/outputs. In subsequent literature there have been various approaches to enable DEA to deal with negative data.     

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested.     

Lessons for O.R. from A.I.: A Scheduling Case Study

This paper compares operational research (O.R.) with the currently fashionable topic of artificial intelligence (A.I.) at a detailed level. A.I. concepts, techniques and history are summarized, and O.R. and A.I. approaches compared. A case study-the development of a potential aid to scheduling repair jobs on RAF squadrons—is described. The paper shows where A.I. concepts and techniques were used in the prototype program, known as the Fault Identification & Expediting Repair (FIXER) system. Finally, some lessons for O.R. are drawn.     

Storage yard operations in container terminals: Literature overview,trends, and research directions

Inbound and outbound containers are temporarily stored in the storage yard at container terminals. A combination of container demand increase and storage yard capacity scarcity create complex operational challenges for storage yard managers. This paper presents an in-depth overview of storage yard operations, including the material handling equipment used, and highlights current industry trends and developments. A classification scheme for storage yard operations is proposed and used to classify scientific journal papers published between 2004 and 2012. The paper also discusses and challenges the current operational paradigms on storage yard operations. Lastly, the paper identifies new avenues for academic research based on current trends and developments in the container terminal industry.