一个多目标的多期数学编程模型,用于整合项目组合优化和承包商选择
Mostafa Zahedirad1, Kaveh Khalili-Damghani1, Vahidreza Ghezavati1
1Department of Industrial Engineering, ST.C., Islamic Azad University, Tehran, Iran.
MethodsX
|August 8, 2025
概括
本研究介绍了项目组合优化和承包商选择的两种方法. 一个同时优化两个方面的集成模型显著优于顺序方法,提供更好的结果和更快的计算.
科学领域:
- 运营研究 运营研究
- 管理科学 管理科学
- 数学优化的数学优化
背景情况:
- 项目组合优化和承包商选择是关键而又复杂的决定.
- 现有的方法往往将这些问题视为单独的问题,可能导致低于最佳的结果.
- 在各种约束下,平衡利,风险和技术能力等多个目标是具有挑战性的.
研究的目的:
- 开发和比较两个不同的建模方法,用于整合项目组合优化和承包商选择.
- 为了评估同步优化模型与顺序方法的有效性.
- 分析拟议方法的计算性能和结果.
主要方法:
- 制定两个混合整数数学编程模型:一个顺序型和一个集成型.
- 应用目标编程 (GP) 来解决多目标优化问题.
- 考虑多个目标 (利,风险,能力,成本) 和限制 (关系,通货膨胀,资源).
- 通过实践案例研究和时间复杂性的分析进行验证.
主要成果:
- 综合模型 (情景2) 与顺序模型 (情景1) 相比,显示出更高的性能.
- 场景2在实现项目和承包商选择目标方面取得了更好的总体结果.
- 综合方法显著提高了CPU时间效率.
结论:
- 通过综合模型同时优化项目组合和承包商选择比顺序方法更有效.
- 目标编程为解决这个领域中复杂的多目标优化问题提供了一个强大的框架.
- 综合模型为战略项目和承包商管理提供了计算效率高且实际上优越的解决方案.
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