Solving a Supply-Chain Management Problem Using a Bilevel Approach

被引:4
作者
Lu, Zhichao [1 ]
Deb, Kalyanmoy [1 ]
Goodman, Erik [2 ]
Wassick, John [3 ]
机构
[1] Michigan State Univ, E Lansing, MI 48824 USA
[2] Michigan State Univ, BEACON Ctr Study Evolut Act, E Lansing, MI 48824 USA
[3] Dow Chem Co USA, Midland, MI 48640 USA
来源
PROCEEDINGS OF THE 2017 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'17) | 2017年
基金
美国国家科学基金会;
关键词
Bi-level optimization; Supply-chain management; Uncertainty handling; Large-scale optimization; GENETIC ALGORITHM; OPTIMIZATION; LOCATION; MODEL;
D O I
10.1145/3071178.3071245
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Supply-chain management problems are common to most industries and they involve a hierarchy of subtasks, which must be coordinated well to arrive at an overall optimal solution. Such problems involve a hierarchy of decision-makers, each having its own objectives and constraints, but importantly requiring a coordination of their actions to make the overall supply chain process optimal from cost and quality considerations. In this paper, we consider a specific supply-chain management problem from a company, which involves two levels of coordination: (i) yearly strategic planning in which a decision on establishing an association of every destination point with a supply point must be made so as to minimize the yearly transportation cost, and (ii) weekly operational planning in which, given the association between a supply and a destination point, a decision on the preference of available transport carriers must be made for multiple objectives: minimization of transport cost and maximization of service quality and satisfaction of demand at each destination point. We propose a customized multi-objective bilevel evolutionary algorithm, which is computationally tractable. We then present results on state-level and ZIP-level accuracy (involving about 40,000 upper level variables) of destination points over the mainland USA. We compare our proposed method with current non-optimization based practices and report a considerable cost saving.
引用
收藏
页码:1185 / 1192
页数:8
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