Study of Suitable Route for Waste Collection: Case Study of Tambon Nong O Sub district Administrative Organization
Main Article Content
Abstract
Currently, the Nong O Subdistrict Administrative Organization has an average amount of solid waste in its area of responsibility of 5 tons per day and it is likely that the amount will continue to increase as the population expands. While there is no uniform waste collection route plan, waste collection takes many hours a day, resulting in wasted budget and energy costs. This research studied the solid waste collection and transportation system of the Nong O Subdistrict Administrative Organization using linear programming and Lingo. In this regard, the goal was to allocate appropriate solid waste transportation routes and analyze the current costs of solid waste collection of the Nong O Subdistrict Administrative Organization to improve and create more efficient waste transportation routes by considering the cost and efficiency of existing garbage trucks as criteria.
The analysis took into account information on the amount of solid waste, collection points, distance, fuel costs, and maintenance costs using linear and Lingo to reduce costs. Originally, the average cost was 1,036.64 baht per day, reduced to 853.95 baht per day, which saved costs 182.72 baht per day, or equivalent to a cost that could be reduced by 17.62%/day. If calculated throughout the fiscal year, government costs would be reduced by up to 66,692 baht. Based on the above information, it could be concluded that the study on the development of a solid waste collection system using linear programming and Lingo to solve vehicle routing problems could actually reduce transportation distance and costs.
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Frederick, S.H. (2010), Introduction to operations research. 9th edition. New York: McGraw-Hill.
Sae-lee, P. and Ritvirool, A. (2014). A Mixed-Integer linear programming model for workforce planning in the Pickled-Ginger production. Naresuan University Engineering Journal, 9(3), 48-54.
Sae-lee, P. and Ritvirool, A. (2014). An integer linear programming model for herbal cosmetic production planning. KMUTT Research and Development Journal, 37(4), 347-360.
Phosamrit, N. and Thammaponphirat, W. (2010). A mathematical model for inventory-routing problem. The Journal of King Mongkut's University of Technology North Bangkok, 20(3), 544-551.
Sirioran, P. (2014). Transportation cost reduction by optimal vehicle routing management a case study: the soft drink business. Panyapiwat Journal, 5, 272-279.
Rapeepan Pitakaso, (2016). Evolutionary method using difference for solving logistics transportation problems. Ubon Ratchathani: Ubon Ratchathani University Press.
Ragsdale, C. T. (2015). Spreadsheet Modeling and Decision Analysis: A Practical Introduction to Business Analytics. 7th edition. Connecticut: Cengage Learning.
Lindo Systems lnc. (2011). Lindo program student version. Retrieved February 9, 2022, from www.lindo.com
Napaporn Thanakamonpradit and Prathana Prathanadee, (2012) “Mixed Integer Linear Programming Model for Yard Location Selection,” 50th Kasetsart University Academic Conference, 31 Jan. -2 Feb. 2012, pp 138-145.
Lindo System lnc, (2014) Lingo 14 Optimization Modeling Software for Linear, Nonlinear and Integer Programming. Retrieved 29 May 29, 2022, from www.lindo.com