IDEAS home Printed from https://ideas.repec.org/a/pcz/alspcz/v7y2013i1p13-20.html
   My bibliography  Save this article

Optimisation Of Knapsack Problem With Matlab, Based On Harmony Search Algorithm

Author

Listed:
  • TAMÁS BÁNYAI

    (University of Miskolc)

  • PÉTER VERES

    (University of Miskolc)

Abstract

The design and operation of logistic systems is a complex problem of engineering. The optimization of logistic systems and processes is the key factor of the economical operation. There are different methods and tools to support this optimization field. The networking of the logistic systems and processes leaded to the development of new heuristic methods and tools to support the optimization of systems with high complexity. A huge number of logistic problems can be related with the knapsack problem. Within the frame of this paper the authors describe the application of harmony search based algorithm with MATLAB fourth-generation programming language to solve the knapsack problem. The authors developed a new bandwidth correction method to this harmony search algorithm, by the aid of which it is possible to control or modify the convergence of the algorithm.

Suggested Citation

  • Tamás Bányai & Péter Veres, 2013. "Optimisation Of Knapsack Problem With Matlab, Based On Harmony Search Algorithm," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 7(1), pages 13-20, December.
  • Handle: RePEc:pcz:alspcz:v:7:y:2013:i:1:p:13-20
    as

    Download full text from publisher

    File URL: http://www.als.zim.pcz.pl/files/ALS7_No1_p13_20_Banyai_Veres.pdf
    Download Restriction: no

    File URL: http://www.als.zim.pcz.pl/7.1.php
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ceylan, Huseyin & Ceylan, Halim & Haldenbilen, Soner & Baskan, Ozgur, 2008. "Transport energy modeling with meta-heuristic harmony search algorithm, an application to Turkey," Energy Policy, Elsevier, vol. 36(7), pages 2527-2535, July.
    2. repec:pcz:journl:v:5:y:2011:i:1:p:57-62 is not listed on IDEAS
    3. Elmaghraby, Salah E., 1989. "The knapsack problem with generalized upper bounds," European Journal of Operational Research, Elsevier, vol. 38(2), pages 242-254, January.
    4. Péter Telek, 2011. "Characteristic Solutions Of Material Flow Systems," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 5(1), pages 57-62, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ágota Bányai, 2013. "Just In Sequence Supply With Multilevel Cross Docking," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 7(2), pages 5-12, December.
    2. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    3. Péter Telek, 2013. "Equipment Preselection For Integrated Design Of Materials Handling Systems," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 7(2), pages 57-66, December.
    4. Ratanavaraha, Vatanavongs & Jomnonkwao, Sajjakaj, 2015. "Trends in Thailand CO2 emissions in the transportation sector and Policy Mitigation," Transport Policy, Elsevier, vol. 41(C), pages 136-146.
    5. Manuel Llorca & José Baños & José Somoza & Pelayo Arbués, 2017. "A Stochastic Frontier Analysis Approach for Estimating Energy Demand and Efficiency in the Transport Sector of Latin America and the Caribbean," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    6. Llorca, Manuel & Baños, José & Somoza, José & Arbués, Pelayo, 2014. "A latent class approach for estimating energy demands and efficiency in transport: An application to Latin America and the Caribbean," Efficiency Series Papers 2014/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    7. Valian, Ehsan & Tavakoli, Saeed & Mohanna, Shahram, 2014. "An intelligent global harmony search approach to continuous optimization problems," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 670-684.
    8. Md Mijanur Rahman & Mohammad Shakeri & Sieh Kiong Tiong & Fatema Khatun & Nowshad Amin & Jagadeesh Pasupuleti & Mohammad Kamrul Hasan, 2021. "Prospective Methodologies in Hybrid Renewable Energy Systems for Energy Prediction Using Artificial Neural Networks," Sustainability, MDPI, vol. 13(4), pages 1-28, February.
    9. Kankal, Murat & AkpInar, Adem & Kömürcü, Murat Ihsan & Özsahin, Talat Sükrü, 2011. "Modeling and forecasting of Turkey's energy consumption using socio-economic and demographic variables," Applied Energy, Elsevier, vol. 88(5), pages 1927-1939, May.
    10. A. Talha Yalta, 2013. "The Dynamics of Road Energy Demand and Illegal Fuel Activity in Turkey: A Rolling Window Analysis," Working Papers 1304, TOBB University of Economics and Technology, Department of Economics, revised Jul 2013.
    11. Altay, Elif Varol & Alatas, Bilal, 2020. "Randomness as source for inspiring solution search methods: Music based approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    12. Sonmez, Mustafa & Akgüngör, Ali Payıdar & Bektaş, Salih, 2017. "Estimating transportation energy demand in Turkey using the artificial bee colony algorithm," Energy, Elsevier, vol. 122(C), pages 301-310.
    13. Geem, Zong Woo, 2011. "Transport energy demand modeling of South Korea using artificial neural network," Energy Policy, Elsevier, vol. 39(8), pages 4644-4650, August.
    14. Kaboli, S. Hr. Aghay & Selvaraj, J. & Rahim, N.A., 2016. "Long-term electric energy consumption forecasting via artificial cooperative search algorithm," Energy, Elsevier, vol. 115(P1), pages 857-871.
    15. Zhao, Jingjing & Heydari, Shahram & Forrest, Michael & Stevens, Alan & Preston, John, 2023. "Investigating correlates of personal and freight road transport energy consumption: A case study of England," Journal of Transport Geography, Elsevier, vol. 112(C).
    16. Hoxha, Julian & Çodur, Muhammed Yasin & Mustafaraj, Enea & Kanj, Hassan & El Masri, Ali, 2023. "Prediction of transportation energy demand in Türkiye using stacking ensemble models: Methodology and comparative analysis," Applied Energy, Elsevier, vol. 350(C).
    17. M Laguna & J Molina & F Pérez & R Caballero & A G Hernández-Díaz, 2010. "The challenge of optimizing expensive black boxes: a scatter search/rough set theory approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 53-67, January.
    18. József Konyha & Tamás Bányai, 2014. "Gprs Based Remote Monitoring System To Support Logistic Decisions," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 8(1), pages 67-76, December.
    19. Tamás Bányai & Péter Veres, 2013. "Optimization Of Production Depth," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 7(2), pages 85-94, December.
    20. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pcz:alspcz:v:7:y:2013:i:1:p:13-20. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Paula Bajdor (email available below). General contact details of provider: https://edirc.repec.org/data/wzpczpl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.