Low volume store planning for workload balancing and truckload
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CitationOkutkan, C., Çelepçıkay, Ö., & Çimen, E. B. (2017). Low volume store planning for workload balancing and truckload. International Logistics and Supply Chain Congress 2017 (pp. 1-7). İstanbul: Dogus University.
In this study, it is aimed to decrease the number of days planned to be shipped in stores with low sales volume, to create a balanced work load and to increase vehicle occupancy capacity . Particularly, Less than Truckload problem is analyzed and model in this study. The techniques used in this study showed that adaptability can be achieved with shipment and store planning as well as green supply chain environment to minimize Less than Truckload (LTL) as well as gas consumption. A mathematical model was created in the direction of multi objective problem and solved in the GAMS environment. Moreover, scenario analyzes were made and the study was tested on five specially identified regions on Turkey.