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:: Volume 8, Issue 1 (4-2017) ::
IJOR 2017, 8(1): 2-14 Back to browse issues page
A Bi-Objective Green Truck Routing and Scheduling Problem in a Cross Dock with the Learning Effect
MirMohammad Musavi , Reza Tavakkoli-Moghaddam , Farnaz Rayat
University of Tehran , mohammad.musavi@ut.ac.ir
Abstract:   (9867 Views)

We present a bi-objective model for a green truck scheduling and routing problem at a cross-docking system. This model determines three key decisions at the cross dock: (1) defining a sequence and schedule of inbound trucks at the receiving door, (2) specifying a sequence and a schedule of outbound trucks at the shipping door, and (3) determining the routes of the outbound truck while serving customers. The first objective function is related to responsiveness of the network that minimizes time window violations and the second objective function minimizes total fuel consumption of trucks in order to consider the environmental factor of the network. Also, a learning effect is considered in loading and unloading process times. To solve the bi-objective model, an archived multi-objective simulated annealing (AMOSA) is used and modified. Finally, a number of test problems are solved and the efficiency of the proposed AMOSA is compared with the e-constraint method.

Keywords: Green truck routing and scheduling, Cross docking, Learning effect, Meta-heuristic algorithm.
Full-Text [PDF 807 kb]   (16384 Downloads)    
Type of Study: Original | Subject: Mathematical Modeling and Applications of OR
Received: 2017/05/11 | Accepted: 2017/11/28 | Published: 2018/04/3
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 8, Issue 1 (4-2017) Back to browse issues page
مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
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