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About

About

Mahdi Homayouni is a Researcher at the Laboratory of Artificial Intelligence and Decision Support ( LIAAD), INESC TEC, Porto, Portugal, since Feb 2017. He has been an Assistant Professor at the Department of Industrial Engineering, Islamic Azad University, Lenjan Branch, Isfahan, Iran, since Feb 2011. 

Mahdi gained his PhD in Industrial and Systems Engineering, from Universiti Putra Malaysia in May 2012. He gained his MSc and BEng degrees in 2008 from Universiti Putra Malaysia, and 2003 from Najafabad Branch- Islamic Azad University- Iran, respectively. He was formerly the head of the Industrial Engineering Department at IAULn, and the director of the young researchers club, IAULn for 2013 to 2016. 

Https://scholar.google.com/citations?user=D0QT05YAAAAJ&hl=en

Https://www.researchgate.net/profile/Seyed_Mahdi_Homayouni?ev=hdr_xprf

Http://www.linkedin.com/profile/preview?locale=en_US&trk=prof-0-sb-preview-primary-button

Http://orcid.org/0000-0001-6833-9316

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Details

Details

  • Name

    Mahdi Homayouni
  • Cluster

    Computer Science
  • Role

    Assistant Researcher
  • Since

    01st February 2017
003
Publications

2019

Joint scheduling of production and transport with alternative job routing in flexible manufacturing systems

Authors
Homayouni, SM; Fontes, DBMM;

Publication

Abstract

2019

A BRKGA for the integrated scheduling problem in FMSs

Authors
Mahdi Homayouni, S; Fontes, DBMM; Fontes, FACC;

Publication
Proceedings of the Genetic and Evolutionary Computation Conference Companion on - GECCO '19

Abstract

2019

Joint production and transportation scheduling in flexible manufacturing systems

Authors
Fontes, DBMM; Homayouni, SM;

Publication
Journal of Global Optimization

Abstract
This work proposes an integrated formulation for the joint production and transportation scheduling problem in flexible manufacturing environments. In this type of systems, parts (jobs) need to be moved around as the production operations required involve different machines. The transportation of the parts is typically done by a limited number of Automatic Guided Vehicles (AGVs). Therefore, machine scheduling and AGV scheduling are two interrelated problems that need to be addressed simultaneously. The joint production and transportation scheduling problem is formulated as a novel mixed integer linear programming model. The modeling approach proposed makes use of two sets of chained decisions, one for the machine and another for the AGVs, which are inter-connected through the completion time constraints both for machine operations and transportation tasks. The computational experiments on benchmark problem instances using a commercial software (Gurobi) show the efficiency of the modeling approach in finding optimal solutions. © 2018 Springer Science+Business Media, LLC, part of Springer Nature

2019

A GENETIC ALGORITHM FOR A MULTI-PRODUCT DISTRIBUTION PROBLEM

Authors
Cretú, B; Faculdade de Economia da Universidade do Porto, Porto, Portugal,; Fontes, DBMM; Mahdi Homayouni, S;

Publication
INTERNATIONAL JOURNAL FOR QUALITY RESEARCH

Abstract
This paper addresses a distribution problem involving a set of different products that need to be distributed among a set of geographically disperse retailers and transported from the single warehouse to the aforementioned retailers. The disfribution and transportation are made in order to satisfy retailers' demand while satisfying storage limits at both the warehouse and the retailers, transportation limits between the warehouse and the retailers, and other operational constraints. This problem is combinatorial in nature as it involves the assignment of a discrete finite set of objects, while satisfying a given set of conditions. Hence, we propose a genetic algorithm that is capable of finding good quality solutions. The genetic algorithm proposed is used to a real case study involving the disfribution of eight products among 108 retailers from a single warehouse. The results obtained improve on those of company's current practice by achieving a cost reduction of about 13%.

2019

Mathematical modelling of multi-product ordering in three-echelon supply chain networks

Authors
Homayouni, SM; Khayyambashi, A; Fontes, DBMM; Fernandes, JC;

Publication
Proceedings of the International Conference on Industrial Engineering and Operations Management

Abstract
This paper proposes a mixed integer linear programming model for a multi-product ordering in a three-echelon supply chain network, where multiple manufacturers supply multiple warehouses with multiple products, which in turn distribute the products to the multiple retailers involved. The model considers practical production constraints such as production capacity, backorder allowances, and economically-viable minimum order quantities. Numerical computations show that the model can efficiently solve small-sized problem instances. © 2019, IEOM Society International.