Conceptual modeling to optimize the haul and transfer of municipal solid waste D.P. Komilis * Laboratory of Solid and Hazardous Waste Management, Department of Environmental Engineering, School of Engineering, Democritus University of Thrace, Xanthi 671 00, Greece Accepted 15 November 2007 Available online 14 January 2008 Abstract Two conceptual mixed integer linear optimization models were developed to optimize the haul and transfer of municipal solid waste (MSW) prior to landfilling. One model is based on minimizing time (h/d), whilst the second model is based on minimizing total cost (€/d). Both models aim to calculate the optimum pathway to haul MSW from source nodes (waste production nodes, such as urban centers or municipalities) to sink nodes (landfills) via intermediate nodes (waste transfer stations). The models are applicable provided that the loca- tions of the source, intermediate and sink nodes are fixed. The basic input data are distances among nodes, average vehicle speeds, haul cost coefficients (in €/ton km), equipment and facilities’ operating and investment cost, labor cost and tipping fees. The time based optimization model is easier to develop, since it is based on readily available data (distances among nodes). It can be used in cases in which no transfer stations are included in the system. The cost optimization model is more reliable compared to the time model provided that accurate cost data are available. The cost optimization model can be a useful tool to optimally allocate waste transfer stations in a region and can aid a community to investigate the threshold distance to a landfill above which the construction of a transfer station becomes financially beneficial. A sensitivity analysis reveals that queue times at the landfill or at the waste transfer station are key input variables. In addition, the waste transfer station ownership and the initial cost data affect the optimum path. A case study at the Municipality of Athens is used to illustrate the presented models. Ó 2007 Elsevier Ltd. All rights reserved. 1. Introduction Mixed integer linear and non-linear programming is valuable decision support tool (DST) in systems optimiza- tion and operational research. Mathematical optimization has been extensively used in various solid waste routing problems, as well as in municipal solid waste (MSW) man- agement systems optimization (Ossenbruggen, 1994). Opti- mizing the haul, transfer and final disposal of MSW through mathematical programming has been a typical optimization problem since the 1970s, when emphasis was given to determining the optimum collection routes (Truitt et al., 1969) as well as to determining facility locations and capacities (Esmaili, 1972; Kirka and Erkip, 1988; Or and Curi, 1993). In addition, optimizing a MSW management system that includes waste processing, such as incineration and recycling, in addition to simple collection–haul–transfer–disposal, has also been tackled extensively in the literature (Gottinger, 1986; Anex et al., 1996; Everett and Modak, 1996; Modak and Everett, 1996; Badran and El-Haggar, 2006). Optimization models on solid waste management have been based on linear pro- gramming, mixed integer and linear programming, mixed integer and non-linear programming and multi-objective programming (Chang and Wei, 1999). Optimization in MSW systems has been mostly achieved by minimizing total cost, with most systems being static rather than dynamic (Badran and El-Haggar, 2006). In a MSW system that includes waste processing, revenues from 0956-053X/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.wasman.2007.11.004 * Tel./fax: +30 2541079391. E-mail address: dkomilis@env.duth.gr www.elsevier.com/locate/wasman Available online at www.sciencedirect.com Waste Management 28 (2008) 2355–2365