Freight Time and Cost Optimization in Complex Logistics Networks
Autor: | Aabir Abubaker Kar, Rachel A. Rigg, Olha Buchel, Amir Akhavan, Alfredo J. Morales, Egemen Sert, Dominic Elias Saadi, Yaneer Bar-Yam, Leila Hedayatifar |
---|---|
Rok vydání: | 2020 |
Předmět: |
0209 industrial biotechnology
021103 operations research Multidisciplinary Article Subject General Computer Science Operations research Computer science business.industry 0211 other engineering and technologies Competitive pressure QA75.5-76.95 02 engineering and technology Finished good Space (commercial competition) 020901 industrial engineering & automation Order (business) Electronic computers. Computer science Manufacturing Production (economics) business Consumer behaviour |
Zdroj: | Complexity, Vol 2020 (2020) |
ISSN: | 1099-0526 1076-2787 |
Popis: | The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to the large number of variables and nonlinear dependencies involved. Here, we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer’s demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. In addition, using customer logistics and thek-means algorithm, we propose additional warehouse locations. For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses. |
Databáze: | OpenAIRE |
Externí odkaz: |