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2758. Optimization with a multi-objective IRP model of the perishable supply chain for fast food restaurants, case of 3PL in Bogota D.C.
Invited abstract in session WC-28: Advancements of OR-analytics in statistics, machine learning and data science 10, stream Advancements of OR-analytics in statistics, machine learning and data science.
Wednesday, 12:30-14:00Room: 065 (building: 208)
Authors (first author is the speaker)
| 1. | JAVIER ENRIQUE MANTILLA ROSAS
|
| CUNDINAMARCA, UNIVERSIDAD DISTRITAL FRANCISCO JOSE DE CALDAS | |
| 2. | Javier Arturo Orjuela Castro
|
| Engineering, Universidad Distrital | |
| 3. | Juan Pablo Orejuela Cabrera
|
| Ing. Industrial., Universidad del Valle |
Abstract
The problem of perishable goods logistics in the fast food sector in the city of Bogota is the shortage and logistics costs of transportation routes for the supply chain carried out by logistics operators, there is a need to analyze the current situation to identify the variables that affect the current results and how to measure the IRP models (Programming, Multi-Objective) for the scheduling and routing of vehicles transporting perishables, in order to satisfy fast food customers (QSR - Quick Service Restaurant), Thus, the delivery of perishable food products (perishables) must have an adequate supply chain to avoid food waste, improve the performance of the agri-food supply chain logistics (AFSC) sector through different optimization models (LIRP, PIRP, IRP), In this research, a mathematical model IRP is defined where G=(N,A), N is the set of vertices and A is the set of arcs, vertex 0 is the supplier, applying the optimization defined by Archetti (2022) IRP (Inventory Routing Problem) whose objective function is to minimize the total inventory cost at the supplier, customers and transportation, where this problem is applied to the QSR sector in order to minimize nonconformities for the FFR (Fast Food Restaurant). The factual problem has 72 restaurants, with 3 multi-temperature products (Frozen, refrigerated and dry), the SLOAD+MCF model was chosen, which incorporates additional multi-product flow constraints with the ability to model the respective demands and capacities.
Keywords
- Logistics
- Programming, Multi-Objective
- Inventory
Status: accepted
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