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124436


#124436 hex color red value is 18, green value is 68 and the blue value of its RGB is 54. Cylindrical-coordinate representations (also known as HSL) of color #124436 hue: 0.45 , saturation: 0.58 and the lightness value of 124436 is 0.17.




124436



Archival data (both digital and physical) that you use in your research or art must be cited just like any other published materials. Every collection, resource (folder), and media file in AILLA has a Persistent Identifier (PID) that must be used in the citation. This PID consists of a namespace (ailla) followed by a six-digit number (e.g., ailla:124436). This number is found at the end of the URI which will be visible in your browser's address bar, e.g. :124436. Note that some browsers will display ":" as "%3A". A search on the PID ailla:124436 in AILLA's digital repository will produce the Kuna Collection of Joel Sherzer. The following guide demonstrates how to cite the different components of AILLA: collections, resources, media files, and static pages.


Cite a collectionSherzer, Joel. Kuna Collection of Joel Sherzer. The Archive of the Indigenous Languages of Latin America, ailla.utexas.org. Access: public. PID ailla:124436. Accessed October 9, 2017.


EconPapers FAQ Archive maintainers FAQ Cookies at EconPapers Format for printing The RePEc blog The RePEc plagiarism page A decision-making tool for integrated order allocation planning and warehouse systems in an incomplete information environmentW. Widowati, S. Sutrisno and Redemtus Heru TjahjanaInternational Journal of Integrated Supply Management, 2022, vol. 15, issue 3, 329-348Abstract:Order allocation planning and inventory management are significant challenges faced when deciding the number of raw materials to purchase from alternative suppliers and store in warehouses for minimal total operational cost. This problem is attributed to incomplete information that makes decision making difficult. Therefore, this study aimed to define problems in an incomplete information environment using fuzzy and probabilistic parameters. Generally, the decision-maker has the data to build their probability distribution functions in probabilistic parameters. However, the available data do not represent the parameters anymore in fuzzy. The parameters include future raw material price, transport cost, and defect rate in manufacturing industries due to fluctuations over time. This study proposed a mathematical optimisation that uses an uncertain linear programming algorithm to calculate the optimal decision. A numerical experiment was performed to illustrate how the problem is solved. The results showed that the proposed model succeeded in determining the optimal decision.Keywords: fuzzy uncertainty; integrated supply chain; inventory management; probabilistic parameter; uncertain programming. (search for similar items in EconPapers)Date: 2022References: Add references at CitEc Citations: Track citations by RSS feedDownloads: (external link) =124436 (text/html)Access to full text is restricted to subscribers.Related works:This item may be available elsewhere in EconPapers: Search for items with the same title.Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/TextPersistent link: :ids:ijisma:v:15:y:2022:i:3:p:329-348Access Statistics for this articleMore articles in International Journal of Integrated Supply Management from Inderscience Enterprises LtdBibliographic data for series maintained by Sarah Parker (Obfuscate( 'inderscience.com', 'informationadministrator5' )). var addthis_config = "data_track_clickback":true; var addthis_share = url:" :ids:ijisma:v:15:y:2022:i:3:p:329-348"Share This site is part of RePEc and all the data displayed here is part of the RePEc data set. Is your work missing from RePEc? Here is how to contribute. Questions or problems? Check the EconPapers FAQ or send mail to Obfuscate( 'oru.se', 'econpapers' ). EconPapers is hosted by the Örebro University School of Business. 041b061a72


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