[Home ] [Archive]    
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Registration ::
Main Menu
Home::
Journal Information::
Articles archive::
Submission Instruction::
Registration::
Submit article::
Site Facilities::
Contact us::
::
Google Scholar

Citation Indices from GS

AllSince 2019
Citations85403575
h-index127
i10-index136

Search in website

Advanced Search
Receive site information
Enter your Email in the following box to receive the site news and information.
:: Search published articles ::
Showing 1 results for Learning Effect

Mr. Mirmohammad Musavi, Dr. Reza Tavakkoli-Moghaddam, Ms. Farnaz Rayat,
Volume 8, Issue 1 (4-2017)
Abstract

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.



Page 1 from 1     

مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
Persian site map - English site map - Created in 0.06 seconds with 27 queries by YEKTAWEB 4645