以竞赛和项目驱动的新工科人才培养的“运筹学”教学模式研究

在新工科人才培养的背景下,传统“以教为中心”的运筹学教学方式,难以实现运筹学以应用为导向的目标。在教学过程中发现教学内容多、学时不够、学习难度大、学习热情低、难以培养学生独立思考和解决问题的能力的问题。为此文章提出以竞赛为目标,项目为驱动的运筹学教学新模式,此教学模式在2016级的交通运输专业的学生中进行了试点。发现此教学模式下,学生正常完成了相应的项目、期末成绩得到了极大的提高,以此项目为基础的作品参加了2019年的全国交通科技大赛,并获得了全国第三的好成绩。此模式极大地鼓舞了学生的自信心、提高了学习能力、增强了个人成就感、让学生有更强的自信去追求更大的梦想。

基于AHM-FCE的“运筹学”课程思政教学评价研究

文章首先阐述了“运筹学”课程思政教学评价指标体系构建,然后提出了基于AHM-FCE的“运筹学”课程思政教学评价模型构建,最后论述了基于AHM-FCE的“运筹学”课程思政教学评价模型应用。

融入人文素养教育的“运筹学”(通识课程)教学研究

人文素养是衡量当代大学生综合素质的重要标准之一,传统“运筹学”教学由于课程性质偏数学或应用数学,往往注重具体的数学理论与方法,无法顾及人文素养方面。在探讨传统“运筹学”课程教学优缺点的基础上,分别从历史观、系统观、哲学观及综合与交叉的角度,论述融入人文素养教育的“运筹学”(通识课程)的教学改革与实践探索。此教学实践能充分激发学生的学习兴趣,启发心智,提升人才培养的综合素质,并获得一系列教学成效,对相关大学课程的教学具有一定的借鉴意义。

OBE理念与翻转课堂融合下的“运筹学”教学研究

为解决交通运输专业“运筹学”课程“以教为中心”的传统教学方式中普遍存在的学生主动性缺乏、学习效率不高、实践应用能力弱等问题,基于OBE教育理念,以成果为导向,以学生能力培养为目标,进行翻转课堂设计,重设教学内容和课时分配,加强案例应用和上机实验,将教学过程分为课前自主学习、课中知识精进及课后反馈与总结三个环节,运用翻转课堂的优势将传统教学中的知识传授提前到课前完成,知识深化及创新应用提到课中,并形成课后多方评价的持续精进机制。从而在有限学时内,对理论性课程的教学做到基础过关、应用加强、自主实践的良好效果,提高学生的自主学习、自主解决问题的能力,为课程教学改革提供了新方向。

针对新工科人才培养的“运筹学”教学模式研究

根据新工科建设需求,分析了当前"运筹学"课程的教学现状,并在此基础上,提出了与新工科人才培养相匹配的教学模式。介绍了新教学模式下的课程目标,并对课程目标进行了分析总结。设计了相应的改革方案,并分别从理论教学、实践教学、案例教学和互动教学四个方面进行详细论述,总结了课程设计思路。该教学模式设计可为日后"运筹学"教学提供一种新思路。

物流管理专业背景下“运筹学”课程思政的教学设计与探索

以物流管理专业为背景,将知识工具、职业素养与德育价值融通,探索物流管理专业背景下运筹学课程思政的教学设计,不仅使学生掌握专业知识,而且提升其文化自信与民族自豪感,培养其对专业的认同感与使命感,树立正确的人生观、价值观。

“运筹学”课程在经济统计应用型本科教学中的探讨

＂运筹学＂是管理类专业的一门实践性非常强的专业基础课程。在多年的经济统计学运筹学课程教学过程中,存在的主要问题是：课程的针对性不明确和应用能力较弱。本文从课程目标、教学内容、教学方法和手段、考核评价方式等方面给出应用型本科经济统计学专业＂运筹学＂教学改革思路和建议。突出对学生实践应用能力的培养,为经济统计学专业＂运筹学＂教学改革提出相关建议,使其符合应用型本科经济统计学专业人才培养的需要。

Effects of Nitrogen Fertilizer Management on Biological Traits and Physiological Indexes at Seedling Stage and Yield of Directly-sown Rapeseed(Brassica napus L.)

Field experiments were carried out to study the effects of different nitroge- napplication rates and application times on biological traits and physiological indexes of directly-sown rapeseed （Brassica napus L.） at the seedling stage and investigate the relationship between these biological traits or physiological indexes at the seedling stage and yield, so as to provide scientific theoretical support for high yield and efficient fertilization management in production of winter rapeseed. Field trials were conducted in Chengdu plain of Sichuan Province under rice-rapeseed rotation system during the period of 2011-2012. The nitrogen application rate trial consisted of five nitrogen levels （0, 90, 180, 270 and 360 kg/hm2） and the nitrogen application time trial included NTl（single application as base fertilized）, NT2 （bottom application ＋one time of topdressing at seedling stage） and NT3 （bottom application＋two times of topdressing at seedling stage） under the same nitrogen rate （225 kg/hm2）. The results indicated that compared with no nitrogen application （NO） treatment, the in- crease of nitrogen fertilizer is beneficial to the increase of biological traits including plant height, green leaf number, leaf area index and dry weight of rapeseed at the seedling stage, the improvement of physiological indexes including total nitrogen content, chlorophyll content and soluble protein content of functional leaves, and the reduction of soluble sugar content. Nitrogen rate was linearly correlated with various biological traits at the seedling stage and physiological indexes including total nitro- gen content, chlorophyll content and soluble sugar content in functional leaves over- a/I, but in parabolic correlation with soluble protein content. Under the same nitrogen rate, NT2 treatment exhibited biological traits remarkably or significantly higher than NT1 treatment and NT3 treatment. The nitrogen application times were linearly cor- related with the physiological indexes of functional leaves at the seedling stage. The various biological traits and physiological index of functional leaves at the seedlings stage were in quadratic function parabolic correlation with seed yield, and the corre- lation was significant （P〈0.05）. Therefore, under the rice-rapeseed rotation system in Chengdu plain, the economic rational nitrogen rate is 180-225 kg/hm2, and the mode of bottom application ＋ one time of topdressing （NT2） is suitable.

Layer-layout-based heuristics for loading homogeneous items into a single container

The container loading problem (CLP) is a well-known NP-hard problem. Due to the computation complexity, heuristics is an often-sought approach. This article proposes two heuristics to pack homogeneous rectangular boxes into a single container. Both algorithms adopt the concept of building layers on one face of the container, but the first heuristic determines the layer face once for all, while the second treats the remaining container space as a reduced-sized container after one layer is loaded and, hence, selects the layer face dynamically. To handle the layout design problem at a layer's level, a block-based 2D packing procedure is also developed. Numerical studies demonstrate the efficiency of the heuristics.

Classifying and ranking DMUs in interval DEA

During efficiency evaluating by DEA, the inputs and outputs of DMUs may be intervals because of insufficient information or measure error. For this reason, interval DEA is proposed. To make the efficiency scores more discriminative, this paper builds an Interval Modified DEA (IMDEA) model based on MDEA. Furthermore, models of obtaining upper and lower bounds of the efficiency scores for each DMU are set up. Based on this, the DMUs are classified into three types. Next, a new order relation between intervals which can express the DM’s preference to the three types is proposed. As a result, a full and more convictive ranking is made on all the DMUs. Finally an example is given.

An Interval Maximum Entropy Method for Quadratic Programming Problem

With the idea of maximum entropy function and penalty function methods, we transform the quadratic programming problem into an unconstrained differentiable optimization problem, discuss the interval extension of the maximum entropy function, provide the region deletion test rules and design an interval maximum entropy algorithm for quadratic programming problem. The convergence of the method is proved and numerical results are presented. Both theoretical and numerical results show that the method is reliable and efficient.

Single-period Two-product Inventory Model with Reorder and Substitution

In market, excess demands for many products can be met by reorder even during one period, and retailers usually adopt substitution strategy for more benefit. Under the retailer＇s substitution strategy and permission of reorder, we develop the profits maximization model for the two-substitutable-product inventory problem with stochastic demands and proportional costs and revenues. We show that the objective function is concave and submodular, and therefore the optimal policy exists. We present the optimal conditions for order quantity and provide some properties of the optimal order quantities. Comparing our model with Netessine and Rudi＇s, we prove that reorder and adoption of the substitution strategy can raise the general profits and adjust down the general stock level.

Optimality Conditions for Static Programming with Generalized Convexity

The definitions of generalized pseudoconvex,generalized quasiconvex and its stri ctly generalized convexity were presented for the static programming at locally star -shaped set using the concept of right-upper derivative and the concept of sub linear. The sufficient and necessary conditions of the static programming were d erived in terms of a generalized Lemma in this paper. The results obtained are u seful for the further study on the duality of static programming and cover many already known conditions.

The revision of classical stock model

On the basis of the analysis of classical stock model, according to the limitation of the model, the article puts forward the revision of classical model and enforces the applicability of the stock model.

THE APPLICATION OF WALSHFUNCTIONS IN SYSTEM ANALYSIS

In this paper,Waish functions are applied to dynamical system analysis. An operational matrix for differential is developed first and compared with M. S. Corrington's method vis a simple example. Then this operational matrix is used to analyze both time-invariant and time-variant systems ,and examples are presented respectively.

Complexity Decision Making and General Systems Theory： An Educational Perspective

The aim of this paper is to look at some important educational aspects of complexity decision making m a mummsc^pnnary manner from the perspective of General Systems Theory （GST）. First, the major issues involved in complexity management and decision making are summarized as they are viewed in literature, and a review of GST and Systems Thinking is given. The discussion in the paper is developed within the context of GST in general, but concentrated on decision making in the three trends of GST： Operations Research, Cybernetics, and Managerial Cybernetics. Here, the role of Cybernetics in complexity decision making is particularly emphasized. The discussion is then extended to the latest developments in complexity decision making in Science of Complexity and Soft Systems Thinking. The study also includes a framework which is expected to guide instructors who are planning to offer contemporary courses on decision making. The framework provides some clues for assessing the level of complexity for a given situation and selecting the appropriate methodology for solution development.

Verifying Ricardo＇s Model--Whether TPP is Right or Wrong？

Through his attempt to clarify justifiable economic circumstances where a policy of globalization and/or a policy of national isolation is proven valid, the author reveals in this thesis that there are two such economic phases： an economy where the theory of comparative advantage, proposed by David Ricardo, is applicable, and an economy where the theory is not applicable. The author applied his original approach to prove the validity of Ricardo＇s comparative advantage theory, and found that the theory can be justified only when a macro economy is in the thetical economic phase, where a policy of globalization is effective. It is a necessary and sufficient condition for the theory to be valid. In other words, Ricardo＇s theory of comparative advantage is not applicable when a macro economy is in the antithetical economic phase, where a policy of national isolation, instead of that of globalization, is valid. The thetical economic phase and the antithetical economic phase of a macro economy, referred to in this thesis by the author, are a version of an expression quite common in OR （operations research）.

TIME SERIES FORECASTING WITH MULTIPLE CANDIDATE MODELS:SELECTING OR COMBINING?

Various mathematical models have been commonly used in time series analysis and forecasting. In these processes, academic researchers and business practitioners often come up against two important problems. One is whether to select an appropriate modeling approach for prediction purposes or to combine these different individual approaches into a single forecast for the different/dissimilar modeling approaches. Another is whether to select the best candidate model for forecasting or to mix the various candidate models with different parameters into a new forecast for the same/similar modeling approaches. In this study, we propose a set of computational procedures to solve the above two issues via two judgmental criteria. Meanwhile, in view of the problems presented in the literature, a novel modeling technique is also proposed to overcome the drawbacks of existing combined forecasting methods. To verify the efficiency and reliability of the proposed procedure and modeling technique, the simulations and real data examples are conducted in this study.The results obtained reveal that the proposed procedure and modeling technique can be used as a feasible solution for time series forecasting with multiple candidate models.

Efficient contraflow algorithms for quickest evacuation planning

The optimization models and algorithms with their implementations on flow over time problems have been an emerging field of research because of largely increasing human-created and natural disasters worldwide.For an optimal use of transportation network to shift affected people and normalize the disastrous situation as quickly and efficiently as possible,contraflow configuration is one of the highly applicable operations research(OR)models.It increases the outbound road capacities by reversing the direction of arcs towards the safe destinations that not only minimize the congestion and increase the flow but also decrease the evacuation time significantly.In this paper,we sketch the state of quickest flow solutions and solve the quickest contraflow problem with constant transit times on arcs proving that the problem can be solved in strongly polynomial time O(nm^2(long n)~2)where n and m are number of nodes and number of arcs,respectively in the network.This contraflow solution has the same computational time bound as that of the best min-cost flow solution.Moreover,we also introduce the contraflow approach with load dependent transit times on arcs and present an efficient algorithm to solve the quickest contraflow problem approximately.Supporting the claim,our computational experiments on Kathmandu road network and on randomly generated instances perform very well matching the theoretical results.For a sufficiently large number of evacuees,about double flow can be shifted with the same evacuation time and about half time is sufficient to push the given flow value with contraflow reconfiguration.

A High-Order Dikin-Type Algorithm for P＊（k）-LCPs in a Wide Neighborhood of the Central Path

Based on the idea of Dikin-type primal-dual affine scaling method for linear program-ming,we describe a high-order Dikin-type algorithm for P_*(κ)-matrix linear complementarity problem in a wide neighborhood of the central path,and its polynomial-time complexity bound is given.Finally,two numerical experiments are provided to show the effectiveness of the proposed algorithms.