Fuzzy Optimization Model for Earthwork Allocations with Imprecise Parameters

• Published in: Journal of construction engineering and management Vol. 133; no. 2; pp. 181 - 190
• Main Authors: Mohamad Karimi, Shahram, Jamshid Mousavi, Seyed, Kaveh, Ali, Afshar, Abbas
• Format: Journal Article
• Language: English
• Published: Reston, VA American Society of Civil Engineers 01-02-2007
• Subjects: Applied sciences; Buildings. Public works; Computation methods. Tables. Charts; Earthwork. Foundations. Retaining walls; Exact sciences and technology; Geotechnics; Road construction. Pavements. Maintenance; Structural analysis. Stresses; TECHNICAL PAPERS; Transportation infrastructure; Computer programming; Parameters; Uncertainty principles; Road construction; Linear programming; Fuzzy set; Modeling; Optimization; Fuzzy sets; Earthworks; Computer program; Earthwork; Example; Application
• ISSN: 0733-9364; 1943-7862
• DOI: 10.1061/(ASCE)0733-9364(2007)133:2(181)

Existing linear programming (LP) models of earthwork allocations in roadway construction assume that unit cost coefficients of earthwork activities and borrow pits/disposal sites capacities are certain and deterministic numbers. However in real-world problems there are naturally some uncertainties inherited in these values, which make it difficult to represent a single value as the candidate of entire possible values. This paper presents a fuzzy linear programming (FLP) model of earthwork allocations based on the fact of assuming unit cost coefficients and borrow pits/disposal sites capacities as fuzzy numbers while minimizing total earth-moving cost as an objective function. A method based on
α
cuts of a fuzzy set is used to take the uncertainty in borrow pits/disposal sites capacities into account. The uncertainty in fuzzy cost coefficients of the objective function and its effects on decision variables of the earthwork allocations model are also considered using the method presented by Chanas and Kuchta in 1994. Subsequently, a more general model is suggested which considers both uncertainties in borrow pits/disposal sites capacities and cost coefficients simultaneously. It is demonstrated that the presented FLP, compared to a deterministic LP, introduces a more robust solution; as the result of giving fuzziness to the uncertain parameters. Such a solution could be beneficial in real world decision making where uncertainties on resources and activities cost exist.