研究生录取问题的双向选择策略

根据问题背景和题目要求研究了在各种不同条件下的研究生录取问题.在对笔试、面试成绩以及导师信息进行量化处理基础上设计了对应的研究生录取方案,通过构造选择矩阵和满意度矩阵建立了双向选择策略的0-1规划模型,借鉴“八皇后”算法思想,采用回溯法编程计算求解出了最优解,得到各问题的最优方案;同时采用降阶技巧和创建的定理,快速地求解出实用的较优解,得到对应较优方案.希望本文提出的解决方案对高等教育部门在高校研究生录取工作中起到一定参考作用.     

研究生录取的优化模型

把研究生录取分解为师生间的评价问题和师生间配对最优化的问题.建立了师生相互评价的指标体系和量化评价指标的计算模型,以满意度计量评价结果,提出了相互满意度的概念,建立了使师生配对达到整体总满意度最大的整数规划优化模型.根据建立的模型,解决了具体的研究生录取问题.所建立的模型具有较强的实用性、可操作性和可扩展性.     

研究生录取问题的一种新数学模型

针对当前研究生录取模型中简单依靠数值放大来统一量纲,或依照经验人为确定各考试环节权值的不足,在采用模糊综合评价法将定性信息定量化的基础上,通过传统的层次分析法确定出各影响指标的权重,建立了一种研究生录取的新模型,并设计了有效的录取方案,最后通过实例验证了该方案的合理性.     

基于最大满意度的研究生录取问题

采用了模糊数学的知识和优化方法讨论解决了研究生的录取问题.首先对相关数据进行了合理的量化,然后定义了导师与学生之间的相互满意度,建立了择优录取和双向选择的优化模型,通过求解得到了理想的结果.     

一种有方案偏好的直觉模糊多属性决策方法

研究了方案属性值和偏好值均为直觉模糊数的多属性决策问题.首先,通过分析部分文献中利用方案属性值与偏好值之间的偏差建立并求解规划模型,从而得到属性权重的不合理性.其次,在最小化方案综合评价值与偏好值偏差的基础上,建立并求解一个规划模型计算出属性权重.然后,利用方案综合评价值的得分函数和准确度函数对方案进行排序,从而得到了一种有方案偏好的直觉模糊数多属性决策方法.最后,通过一个实例说明了该方法的合理性与有效性.     

调剂问题的Vague指派方法研究

调剂工作是硕士研究生招生录取过程中一项非常重要的工作.论文以硕士研究生调剂工作为例,通过分析基本特征,将其转化为指派问题进行研究.并借助于Vague集思想,运用面试投票的方法获得效益矩阵.根据评价者的不同偏好特征采用记分函数将Vague值转化为实数,得到了实数满意度矩阵.进而不仅实现了学生和录取单位的共赢,也实现了资源的优化配置.该方法一方面为此类问题的解决提供了一种有效途径,另一方面也在理论上找到了Vague指派的一般步骤,通过数据计算保证了该方法在问题解决上的有效性和可行性.     

大规模定制模式下具有直觉模糊信息的生产指派问题研究

针对大规模定制模式下生产指派面临的模糊不确定性等问题,探讨企业如何在现有生产能力限制条件下,运用直觉模糊理论构建生产指派模型进而确定最满意的生产指派方案.首先,根据TOPSIS原理,定义了直觉模糊决策矩阵行向量、列向量的正理想点与负理想点,以及行相对相似度、列相对相似度与综合相对相似度并据此建立了顾客个性化需求目标函数.然后,构建了以满足顾客个性化需求以及企业利润最大化为目标的多目标整数规划模型,并探讨其求解方法与过程.最后,通过一个算例来说明模型的求解过程及其有效性、合理性.     

指派问题在供应商选优决策中的应用

通常供应链中供应商选优问题为多指标决策问题,本将此问题视为指派问题。指派问题中的关键是确定“效率”矩阵,本充分利用供应商单排序结果,评价指标权重以及供应商指标评价值构造了“效率”矩阵,建立了供应商综合选优指派问题模型,案例试算表明该方法合理、有效,为多指标方案决策提供了又一种可行的决策方法。     

基于0-1规划的群模糊层次分析法

根据指派问题模型的思想将单模糊层次分析法推广到群模糊层次分析法,建立了基于0-1规划的群模糊层次分析法模型。然后以历届全国大学生数学建模竞赛试题质量的综合评价指标体系为例,给出了这种方法的计算结果,并与基于加权平均的群模糊层次分析法的计算结果进行了对比分析,说明了基于0-1规划的群模糊层次分析法的有效性和优越性。     

大规模定制模式下基于三角直觉模糊信息的生产指派问题研究

针对大规模定制模式下生产指派面临的模糊不确定性等问题,探讨如何运用三角直觉模糊数构建生产指派模型进而确定最满意的生产指派方案。首先,运用三角直觉模糊数刻画、设计基于顾客个性化需求与企业产出的相对偏差、产品价格与交货期等影响因素的顾客满意度函数和企业利润函数。其次,建立了兼顾企业利润和顾客满意度的调和函数,据此构建了生产指派模型,并证明该模型有可行解和最优解,然后说明模型的求解方法。最后,通过具体实例说明生产指派模型的求解过程及其有效性、合理性。     

Formulating and solving production planning problems

Production planning problems frequently involve the assignment of jobs or operations to machines. The simplest model of this problem is the well known assignment problem (AP). However, due to simplifying assumptions this model does not provide implementable solutions for many actual production planning problems. Extensions of the simple assignment model known as the generalized assignment problem (GAP) and the multi-resource generalized assignment problem (MRGAP) have been developed to overcome this difficulty. This paper presents an extension of the (MRGAP) to allow splitting individual batches across multiple machines, while considering the effect of setup times and setup costs. The extension is important for many actual production planning problems, including ones in the injection molding industry and in the metal cutting industry. We formulate models which are logical extensions of previous models which ignored batch splitting for the problem we address. We then give different formulations and suggest adaptations of a genetic algorithm (GA) and simulated annealing (SA). A systematic evaluation of these algorithms, as well as a Lagrangian relaxation (LR) approach, is presented.     

广义指派问题及其在军事装备运输中的推广应用

军事装备中的运输问题复杂多样,如何建立数学模型是寻求优化方案的关键.本文首先将最优线性指派模型推广到广义指派模型并给出其两种算法,其次对带有时间约束的运输问题进行建模,并设法将其转化为广义指派问题来处理,从而为这类运输问题提供了一种有效可行的算法.     

A study of decision support models for online patient-to-room assignment planning

The present paper studies patient-to-room assignment planning in a dynamic context. To this end, an extension of the patient assignment (PA) problem formulation is proposed, for which two online ILP-models are developed. The first model targets the optimal assignment for newly arrived patients, whereas the second also considers future, but planned, arrivals. Both models are compared on an existing set of benchmark instances from the PA planning problem, which serves as the basic problem setting. These instances are then extended with additional parameters to study the effect of uncertainty on the patients’ length of stay, as well as the effect of the percentage of emergency patients. The results show that the second model provides better results under all conditions, while still being computationally tractable. Moreover, the results show that pro-actively transferring patients from one room to another is not necessarily beneficial.     

Development of a new approach for deterministic supply chain network design

This paper proposes a mixed integer linear programming model and solution algorithm for solving supply chain network design problems in deterministic, multi-commodity, single-period contexts. The strategic level of supply chain planning and tactical level planning of supply chain are aggregated to propose an integrated model. The model integrates location and capacity choices for suppliers, plants and warehouses selection, product range assignment and production flows. The open-or-close decisions for the facilities are binary decision variables and the production and transportation flow decisions are continuous decision variables. Consequently, this problem is a binary mixed integer linear programming problem. In this paper, a modified version of Benders’ decomposition is proposed to solve the model. The most difficulty associated with the Benders’ decomposition is the solution of master problem, as in many real-life problems the model will be NP-hard and very time consuming. In the proposed procedure, the master problem will be developed using the surrogate constraints. We show that the main constraints of the master problem can be replaced by the strongest surrogate constraint. The generated problem with the strongest surrogate constraint is a valid relaxation of the main problem. Furthermore, a near-optimal initial solution is generated for a reduction in the number of iterations.     

Discrete time dynamic traffic assignment models and solution algorithm for managed lanes

“Managed” lanes of highways usually refer to lanes that are not open to all types of vehicles, such as “High Occupancy Vehicles” (HOV) lanes and “High Occupancy Toll” (HOT) lanes, etc. The HOV lanes of highways are reserved only for vehicles with a driver and one or more passengers. Whereas, HOT lanes allow all vehicles but require tolls from the vehicles with no passenger except the driver. In this paper, we present a discrete-time traffic assignment system optimum model to predict the optimal traffic flows on managed lanes at various times in the entire planning horizon. This model minimizes the overall delay (travel time) and belongs to the class of dynamic traffic assignment (DTA) problems. When applied to general networks, DTA problems can be large and difficult to solve, but the problem is manageable when it is applied to a network with managed lanes. In particular, the DTA model in this paper for managed lanes is reduced to a mixed integer program for which several efficient heuristic algorithms exist. This paper also discusses the special properties of the discrete-time DTA model, based upon which a heuristic algorithm is proposed. Numerical results show that this algorithm is efficient for many cases of the managed lane problems.     

An extended assignment problem considering multiple inputs and outputs

The existing assignment problems for assigning n jobs to n individuals are limited to the considerations of cost or profit incurred by each possible assignment. However, in real applications, various inputs and outputs are usually concerned in an assignment problem, such as a general decision-making problem. This paper develops a procedure for resolving assignment problems with multiple incommensurate inputs and outputs for each possible assignment. The concept of the relative efficiency in using various resources, instead of cost or profit, is adopted for each possible assignment of the problem. Data envelopment analysis (DEA) is employed in this paper to measure the efficiency of one assignment relative to that of the others according to a set of decision-making units. A composite efficiency index, consisting of two kinds of relative efficiencies under different comparison bases, is defined to serve as the performance measurement of each possible assignment in the problem formulation. A mathematical programming model for the extended assignment problem is proposed, which is then expressed as a classical integer linear programming model to determine the assignments with the maximum efficiency. A numerical example is used to demonstrate the approach.     

求解二次分配问题的新的流量模型

二次分配问题是具有广泛应用背景的经典组合优化难题之一。本文在二次分配问题已有线性化模型的基础上,提出了一种新的基于流量的线性化模型。数值试验结果表明,新模型无论从时间上还是计算节点数都更具有优势。     

军用飞机维修质量管理的最优线性分派评估

在军机维修工作中,科学有效的管理,对及时完成维修任务,保障训练作战计划至关重要.在建立适合我军军机维修质量评估指标体系的基础上,定义了理想方案和贴近度,给出了排序频数的计算方法,进而将军机维修质量评估问题转化为最优线性分派问题来处理,从而为军机维修质量管理提供了一种科学、可靠的决策方法.     

双层指派模型及算法

介绍了指派问题应用中出现的一种新类型——双层指派问题,建立了双层指派问题的数学模型,并提出了针对双层指派模型的算法,最后给出它在铁路客车车底周转运用中的实例.