Refine your search
Collections
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Karmaker, C. L.
- A Decision Support System for Warehouse Location Selection:A Case Study
Abstract Views :297 |
PDF Views:0
Authors
Affiliations
1 Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology, Dhaka, BD
1 Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology, Dhaka, BD
Source
Journal of Supply Chain Management Systems, Vol 5, No 4 (2016), Pagination: 27-37Abstract
The main aim of this research is to develop a decision support system for determining warehouse location. An anticipated model is constructed with fuzzy extension of the Analytic Hierarchy Process (FAHP) and fuzzy extension of the Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) methods. In this article 16sub-criteria divided in 5 main groups are taken for location decision model collected from literatures review and practical investigations in the distribution arena in Bangladesh.The weights of the sector and subsector are estimated by FAHP method and using FTOPSIS, eligible locations are ranked according to the results. Finally, an empirical study for warehouse location-allocation problem of the retail chain of Rahimafrooz Superstore Ltd. (RSL) named Agora in Bangladesh is presented to visualize the methodologies and effectiveness of the model proposed by this paper.Keywords
Location Choice, Fuzzy Multi-Criteria Decision, Fuzzy AHP, Fuzzy TOPSIS, Retail Chain.- Analysis of Different Inventory Control Techniques:A Case Study in a Retail Shop
Abstract Views :464 |
PDF Views:1
Authors
Affiliations
1 Department of Industrial and Production Engineering, Jessore University of Science and Technology, Jessore, BD
1 Department of Industrial and Production Engineering, Jessore University of Science and Technology, Jessore, BD
Source
Journal of Supply Chain Management Systems, Vol 6, No 3 (2017), Pagination: 35-45Abstract
The inventory of materials constitutes the most significant part of current assets and working capital in any organisation. A small saving in the inventory will mirror a crucial edge in benefit of the organisation. In Bangladesh, the retail shops generally face two types of inventory related problems which are either stock-out or overstock. As a result, most of the shops fail to maintain their product availability with lowest possible inventory cost. Through proper inventory control techniques, probability of stock-out as well as overstock situations in the retail shops can be minimised. The present paper is a case study of different inventory control techniques for efficient inventory management system of a retail shop of Bangladesh. The sole purpose of the study is to provide a guideline for inventory managers that will help them to ensure product availability at right quantity as and when required. Relevant data were collected from a renowned retail shop, namely, Pran RFL group, Bangladesh. This real case demonstration will certainly help the future researchers as well as the Bangladeshi manufacturers to maintain proper control & management of inventories.Keywords
Inventory Control, Profit, Stock-Out, Overstock, Retail Shop.References
- Chase, R. B., Jacobs, F. R., & Aquilano, N. J. (2008). Operations and supply management (12th ed.). New York: The McGraw-Hill / Irwin.
- Chen, W. Z., Hung, L. C., Fu, F. E., & Peng, S. S. (2012). An abc analysis model for the multiple products inventory control - A case study of company X. Proceedings of the Asia Pacific Industrial Engineering & Management Systems Conference, pp. 495-503.
- Hatefi, S. M., Torabi, S. A., & Bagheri, P. (2014). Multicriteria ABC inventory classification with mixed quantitative and qualitative criteria. International Journal of Production Research, 52(3), 776-786.
- Heizer, J., & Barry, R. (2011). Operation management (10th ed.). United States of America: Pearson Prentice Hall.
- Johson, R. A., Newell, W. T., & Vergin, R. C. (1974). Production and operations management. London: Houghton Mifflin Company.
- Jose, T., Jayakumar, A., & Sijo, M. T. (2013). Analysis of inventory control techniques: A comparative study. International Journal of Scientific and Research Publications, 3(3), 1-6.
- Kumar, P., & Anas, M. (2013). An ABC analysis for the multiple products inventory management case study of scooters India limited. IJREAT International Journal of Research in Engineering & Advanced Technology, 1(5), 1-6.
- Kumar, Y., Lilhare, A., Sahu, A., Lal, B., Sinha, T., Khaparde, Y., & Janghel, S. (2016). HML Analysis for Inventory Management-Case Study of Steel Plant. International Journal for Research in Applied Science & Engineering Technology (IJRASET), 4(3), 521-526.
- Lee, H. H., & Kleiner, B. H. (2001). Inventory management in women’s retail clothing industry. Management Research News, 24(3/4), 40-44.
- Mahant, H., Chouhan, S. S., & Yadav, A. (2013). Inventory management by implementation of ABC analysis upon medium scale industry. International Journal of Scientific Research, 2(8), 162-165.
- Mitra, S., Pattanayak, S. K., & Bhowmik, P. (2013). Inventory control using ABC and HML analysis – A case study on a manufacturing industry. International Journal of Mechanical and Industrial Engineering, 3(1), 37-42.
- Mitra, S., Reddy, M. S., & Prince, K. (2015). Inventory control using FSN analysis - A case study on a manufacturing industry. International Journal of Innovative Science, Engineering & Technology, 2(4), 322-325.
- Mwangi, A. G. (2013). Inventory Management and Supply Chain Performance of Non-Governmental Organizations in the Agricultural Sector, Kenya. Thesis Masters, University of Nairobi, Kenya.
- Rambabu, B., & Malyadri, G. (2014). A study on inventory management at Amara Raja Electronics Ltd, Tirupati. Global Journal for Research Analysis, 3(1), 44-47.
- Raphella, A., Nathan, G., & Chitra, G. (2014). Inventory management: A case study. International Journal of Emerging Research in Management & Technology, 3(3), 94-102.
- Ravinder, H., & Misra, R. B. (2014). ABC analysis for inventory management: Bridging the gap between research and classroom. American Journal of Business Education - Third Quarter, 7(3), 257-264.
- Sukhia, K. N., Khan, A. A., & Bano, M. (2014). Introducing economic order quantity model for inventory control in web based point of sale applications and comparative analysis of techniques for demand forecasting in inventory. Management International Journal of Computer Applications, 107(19), 1-8.
- Tahir, N., & Choudhary, M. A. (2011). Development of a Decision Support System for Inventory Analysis and Control. IEEE Int’l Technology Management Conference, 2(5), 864-876.
- Verma, P. (2010). Inventory Management of Selected Shipyard Companies in India, thesis PhD, Saurashtra University.
- Supply Chain Contract Selection Using Delphi- Based AHP: A Case Study in the Bangladeshi Super Shop
Abstract Views :225 |
PDF Views:0
Authors
Affiliations
1 Department of Industrial and Production Engineering, Jashore University of Science and Technology, Jashore, BD
1 Department of Industrial and Production Engineering, Jashore University of Science and Technology, Jashore, BD
Source
Journal of Supply Chain Management Systems, Vol 8, No 3 (2019), Pagination: 37-47Abstract
Selection of the best supply chain contract plays a significant role as a strategic feature and factor of better coordination of all stages in a supply chain. As a variety of uncontrollable and unpredictable factors affect the evaluation and decision-making process at different levels, identification of the most appropriate contract is usually very complex and unstructured. In this paper, Delphi-based analytic hierarchy process (AHP) approach has been proposed to tackle the problem. The sole purpose of the paper is to analyse the existing contracts of the organisation and recommend the best one. Necessary data of powdered milk item were collected from a renowned super shop in Bangladesh, namely, Swapno superstore, Dhaka. In order to demonstrate the applicability of the proposed approach, an illustrative example is presented; the result is analysed at the end of this paper. This work can be a guide for Bangladeshi planners as well as other researchers to identify the most suitable agreement for their supply chain.Keywords
AHP, Delphi, Multi-Criteria Decision-Making, Supply Chain Contract.References
- Aguezzoul, A., & Pires, S. (2016). 3PL performance evaluation and selection: A MCDM method. Supply Chain Forum: An International Journal, 17(2), 87-94. Taylor & Francis.
- Al-Odeh, M. (2016). Supply chain information systems technologies and management strategies in northern minnesota. Journal of Supply Chain Management Systems, 5(2), 22-37.
- An, R. (2016). Supply chain analytics and competitive advantage: An empirical study of the Indian automobile industry. Journal of Supply Chain Management Systems, 5(4), 45-55.
- Azadfallah, M. (2017). Multi criteria supplier selection using PROMETHEE outranking procedures. Journal of Supply Chain Management Systems, 6(1), 24-32.
- Bansal, M., Karimi, I. A., & Srinivasan, R. (2007). Optimal contract selection for the global supply and distribution of raw materials. Industrial & Engineering Chemistry Research, 46, 642-660.
- Becker-Peth, M., & Thonemann, U. W. (2016). Reference points in revenue sharing contracts. How to design optimal supply chain contracts. European Journal of Operational Research, 249(3), 1033-1049.
- Calfa, B. A., & Grossmann, I. E. (2015). Optimal procurement contract selection with price optimization under uncertainty for process networks. Computers & Chemical Engineering, 82, 330-343.
- Chandak, A., Chandak, S., & Dalpati, A. (2018). A study of impact of supply chain strategy on supply chain performance: An empirical investigation on automobile industry in India. Journal of Supply Chain Management, 7(3), 01-07.
- Feng, Y., Martel, A., D’Amours, S., Beauregard, R., (2013). Coordinated contract decisions in a maketoorder manufacturing supply chain: A stochastic programming approach. Production and Operations Management, 22, 642-660.
- Forkmann, S., Henneberg, S. C., Naude, P., & Mitrega, M. (2016). Supplier relationship management capability: A qualification and extension. Industrial Marketing Management, 57, 185-200.
- Govindan, K., Kaliyan, M., Kannan, D., & Haq, A. N. (2014). Barriers analysis for green supply chain management implementation in Indian industries using analytic hierarchy process. International Journal of Production Economics, 147, 555-568.
- Jin, Y., Wang, S., & Hu, Q. (2015). Contract type and decision right of sales promotion in supply chain management with a capital constrained retailer. European Journal of Operational Research, 240(2), 415-424.
- Joseph, B. M., & James, N. (2018). A hybrid AHP and taguchi loss function method for supplier selection. Journal of Supply Chain Management Systems, 7(4), 20-30.
- Kailash, Saha, R. K., & Goyal, S. (2019). Factors analysis of ISCM benchmarking using DEMATEL technique. Journal of Supply Chain Management Systems, 8(1), 1-14.
- Karmaker, C. L. (2016). A decision support system for warehouse location selection: A case study. Journal of Supply Chain Management Systems, 5(4), 27-37.
- Khalilpour, R., & Karimi, I. A. (2011). Selection of Liquefied Natural Gas (LNG) contracts forminimizing procurement cost. Industrial & Engineering Chemistry Research, 50, 10298-10312.
- Khalilpour, R., & Karimi, I. A. (2012). Contract selection under uncertainty: LNG buyers’ perspective. Computer Aided Chemical Engineering, 31, 1487-1491.
- Li, J. C., Zhou, Y. W., & Huang, W. (2017). Production and procurement strategies for seasonal product supply chain under yield uncertainty with commitmentoption contracts. International Journal of Production Economics, 183, 208-222.
- Li, Y. L., Ying, C. S., Chin, K. S., Yang, H. T., & Xu, J. (2018). Third-party reverse logistics provider selection approach based on hybrid-information MCDM and cumulative prospect theory. Journal of Cleaner Production, 195, 573-584.
- Liu, Z., Zhao, R., Liu, X., & Chen, L. (2017). Contract designing for a supply chain with uncertain information based on confidence level. Applied Soft Computing, 56, 617-631.
- Lootsma, F. A. (1999). Multi-criteria decision analysis via ratio and difference judgment. Kluwer Academic Publishers.
- Matsuo, H. (2015). Implications of the Tohoku earthquake for Toyota ׳s coordination mechanism: Supply chain disruption of automotive semiconductors. International Journal of Production Economics, 161, 217-227.
- O’Brien, J. (2018). Supplier relationship management: Unlocking the hidden value in your supply base. Kogan Page Publishers.
- Park, M., Park, S., Mele, F. D., & Grossmann, I. E. (2006). Modeling of purchase and sales contracts in supply chain optimization. Industrial & Engineering Chemistry Research, 45, 5013-5026.
- Prakash, C., & Barua, M. K. (2016). A combined MCDM approach for evaluation and selection of third-party reverse logistics partner for Indian electronics industry. Sustainable Production and Consumption, 7, 66-78.
- Raut, R., Kharat, M., Kamble, S., & Kumar, C. S. (2018).Sustainable evaluation and selection of potential thirdparty logistics (3PL) providers: An integrated MCDM approach. Benchmarking: An International Journal, 25(1), 76-97.
- Rodríguez, M. A., & Vecchietti, A. (2012). Mid-term planning optimization model with sales contracts under demand uncertainty. Computers & Chemical Engineering, 47, 227-236.
- Rodríguez, M. A., & Vecchietti, A. (2009). Logical and generalized disjunctive programming for supplier and contract selection under provision uncertainty. Industrial & Engineering Chemistry Research, 48, 5506-5521.
- Saaty, T. L. (1994). Homogeneity and clustering in AHP ensures the validity of the scale. European Journal of Operational Research, 72(3), 598-601.
- Tsay, A. A., Nahmias, S., & Agrawal, N. (1999). Modeling supply chain contracts: A review. In Tayur, S., Ganeshan, & R., Magazine, M. (Eds.), Quantitative Models for Supply Chain Management. Springer US. International Series in Operations Research & Management Science, 17, 299-336.
- Wang, C. X. (2002). A general framework of supply chain contract models. Supply Chain Management: An International Journal, 7(5), 302-310.