Optimization Modeling for Logistics: Options and Implementations

被引:33
|
作者
Bartolacci, Michael R. [1 ]
LeBlanc, Larry J. [2 ]
Kayikci, Yasanur [3 ]
Grossman, Thomas A. [4 ]
机构
[1] Penn State Univ Berks, Reading, PA 19610 USA
[2] Vanderbilt Univ, Owen Grad Sch Management, Nashville, TN USA
[3] Univ Min & Met Leoben, Ind Logist Dept, A-8700 Leoben, Austria
[4] Univ Sao Francisco, BR-12900000 Braganca Paulista, SP, Brazil
关键词
optimization; spreadsheets; USES OPERATIONS-RESEARCH; SUPPLY CHAIN MODEL; DESIGN; MANAGEMENT; NETWORK; TRANSPORT; SYSTEMS;
D O I
10.1111/j.0000-0000.2012.01044.x
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Logistics optimization has significantly grown in popularity over the last few decades. Improvements in computing power, modeling software, and the willingness of companies to invest time in the modeling effort have allowed models that were once too unwieldy to solve to optimality to be solved quickly. This has led to a more wide-spread recognition by logistics managers of the potential advantages of using optimization. The scope of logistics optimization in companies and organizations has expanded to address strategic, tactical, operational, and collaborative decision making. Spreadsheets, an analytical tool familiar to managers, have played a crucial role in the expanded modeling efforts of companies. Although optimizations role in logistics has grown tremendously, there still are areas that remain to be explored that will allow it to achieve an even larger and more successful role in the management of companies. Additionally, there are some models that are still too large or too complex to currently solve to optimality, despite the advances in computing power and modeling/solving software.
引用
收藏
页码:118 / 127
页数:10
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