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Title: Bi-objective Optimization for Joint Production Scheduling and Distribution Problem with Sustainability
Authors: Yağmur, Ece
Kesen, Saadettin Erhan
Keywords: Joint Production And Distribution Scheduling
Vehicle Routing
Job Shop
Heterogeneous Fleet
Mixed Integer Model
Integrated Production
Issue Date: 2021
Abstract: This paper considers joint production and distribution planning problem with environmental factors. While the production phase of the problem consists of job shop production environment running under Just-In-Time (JIT) philosophy, the distribution phase involves a heterogeneous fleet of vehicles with regards to capacity and fuel consumption rate. Therefore, we tackle two well-known problems in Operations Research terminology which are called machine scheduling and vehicle routing problems. The joint problem is formulated as a bi-objective structure, the first of which is to minimize the maximum tardiness, the second of which aims to minimize the total amount of CO2 emitted by the vehicles. Orders are required to be consolidated to reduce the traveling time, distance, or cost. An increase in the vehicle capacity results in a higher possibility of consolidation, but in this case, the amount of CO2 emission that the vehicle emits into the air will also increase. Having shown that two objectives are conflicting in an illustrative example, we formulate the problem as amixed integer programming (MIP) formulation and use an Augmented Epsilon Constraint Method (AUGMECON) for solving the bi-objective model. On randomly generated test instances, the applicability of the MIP model through the use of AUGMECON is reported.
Description: 12th International Conference on Computational Logistics (ICCL) -- SEP 27-29, 2021 -- ELECTR NETWORK
ISBN: 978-3-030-87672-2; 978-3-030-87671-5
ISSN: 0302-9743
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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