Data on A Goal Programming Model for Optimizing the Reverse Logistics Network of Glass Containers, and an Application in Turkey

Published: 09-03-2021| Version 3 | DOI: 10.17632/dkf65jd9fc.3
Contributors:
Raci Berk Islim,
Sule Itir Satoglu

Description

Since there is no data available in the literature or through internet, we really made an effort to find real data and try to estimate non-available data through available ones, correctly. Scalar and parameters of the mathematical model in the study are estimated according to assumptions shown as below, and are given in folders. Assumptions • There are 3 source of glass containers. These are from recycle bins, HORECA and other waste recyclers, and those amounts are estimated according to some past data. • All cost parameters are foreknown which are calculated from real data, and will be shown in detail. • Cost parameters will be determined with estimated inflation rate for the future periods and revenue parameters will be determined according to government payments per ton of recycled glass. • Glass container consumption is directly proportional with the population of a town. So, for districts in which this data does not exist, the amount of glass can be collected through recycle bins is estimated according to their populations. • The glass container source from other recyclers are assumed as 10% of total amount of glass containers available through recycle bins in each period. • At the beginning of first period, 10 million Turkish Liras (TL) budget is available. Thereby, Bp parameter becomes 10,000,000 for the first period and 0 for the rest of periods. • For operational side of glass recycling facility, we have stayed in touch with a real firm named “Cam Kırığı” located in Gebze/Istanbul through telephone interviews to get data (telephone interview, March 2019). • The information about the glass manufacturer belongs to Sisecam Company, which is biggest glass manufacturer in Turkey. • Equivalent cost parameters for future periods will be adjusted according to official price increases and inflation expectations. • 1 year consists of 250 workdays. So, WD scalar becomes 250. • Distances between facilities and glass container sources are based on highway routes. • One driver and one assistant are required for each truck type 1 whereas only a driver is needed for truck type 2. So, these are summed with the required number of workers in the facility in order to find total number of personnel.

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