Four-dimensional Gradient Integration: Reform and Practice on Modeling and Simulation Courses for Management Disciplines

doi:10.16182/j.issn1004731x.joss.26-0058

Abstract

Abstract:

In the process of course implementation, local universities generally face problems such as students' weak mathematical and physical foundations, disconnection between teaching content and technological frontiers, single teaching method, and fragmented cultivation of practical capability. Based on long-term teaching reform practice, a four-dimensional gradient integration teaching model of "value guidance, knowledge restructuring, scenario innovation, and capability progression" was proposed, and its theoretical logic, implementation path, and practical effect were systematically elaborated. This model can effectively stimulate students' intrinsic motivation for learning, promote the digital and intelligent updating of teaching content, expand the teaching scenario of industry-education integration, and realize the progressive improvement of students' practical innovation capability. It has positive demonstrative significance and promotional value for the reform of modeling and simulation courses.

Key words: modeling and simulation course, four-dimensional gradient integration, industry-education integration, management major, OBE philosophy

CLC Number:

TP391.9

Wu Bin, Tong Huagang, Cui Zhiyong, Yan Feiyi. Four-dimensional Gradient Integration: Reform and Practice on Modeling and Simulation Courses for Management Disciplines[J]. Journal of System Simulation, 2026, 38(6): 1528-1534.

Figures/Tables 5

Fig. 1

Table 1

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Table 2

Intelligent job shop scheduling simulation optimization case

教学维度	教学设计
价值引领：将学习使命锚定于国家战略与产业痛点，建立“为提升制造业智能化水平建模与仿真”的使命感	以我国“智能制造”战略为背景，剖析车间调度作为制造系统“大脑”的关键作用。通过展示因调度不力导致交付延误、资源浪费的真实企业案例，引导学生理解仿真优化对提升国家制造业竞争力的管理价值与社会责任
知识重构：知识核心从“仿真参数设置”转向“管理目标建模”与“智能决策算法集成”，构建“问题-模型-算法”的认知链条	弱化对仿真引擎底层算法的纠缠；强化如何将调度问题抽象为“工件、机器、工序、目标”等核心要素。重点讲解如何将最小化最大完工时间、提高设备利用率等管理目标，转化为仿真模型中的性能指标与优化目标，并引入遗传算法、模拟退火等智能调度算法作为对比
情景创新：在动态不确定性的管理情境中，训练学生运用仿真作为分析工具和“决策实验场”，权衡效率、成本、客户满意度等多重目标	创设“多品种、小批量、急插单”的柔性生产情景。提供真实的生产订单数据与设备信息，设定“关键客户订单突然提前”等动态扰动。要求学生通过仿真，评估“先到先得”“最短加工时间”等传统规则与智能算法的优劣，并设计抗扰动的调度方案
能力进阶：通过“基础建模→动态分析→创新优化”的阶梯式任务链，驱动能力从“能建模型”向“能用模型发现管理规律、支持优化决策”的系统工程思维跃迁	1. 课程作业：完成一个静态车间(无扰动)的基础仿真模型 2. 综合实训：小组合作，在上述动态情景中，对比至少3种调度策略，撰写分析报告 3. 学科竞赛/科研延伸：成果优秀的学生继续挑战创新性课题，如“考虑AGV运输或数字孪生的车间调度优化”，冲刺学科比赛或撰写学术论文

Table 2

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