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Privatization of municipal solid waste (MSW) collection can improve service quality and reduce cost. To reduce the risk of an incapable company serving an entire collection area and to establish a competitive market, a large collection area should be divided into two or more subregions, with each subregion served by a different company. The MSW subregion districting is generally done manually, based on the planner's intuition. Major drawbacks of a manual approach include the creation of a districting plan with poor road network integrity for which it is difficult to design an efficient collection route. The other drawbacks are difficulty in finding the optimal districting plan and the lack of a way to consistently measure the differences among subregions to avoid unfair competition. To determine an MSW collection subregion districting plan, this study presents a mixed-integer optimization model that incorporates factors such as compactness, road network integrity, collection cost, and regional proximity. Two cases are presented to demonstrate the applicability of the proposed model. In both cases, districting plans with good road network integrity and regional proximity have been generated successfully.

Separating recyclables from municipal solid waste (MSW) before collection reduces not only the quantity of MSW that needs to be treated but also the depletion of resources. However, the participation of residents is essential for a successful recycling program, and the level of participation usually depends on the degree of convenience associated with accessing recycling collection points. The residential accessing convenience (RAC) of a collection plan is determined by the proximity of its collection points to all residents and its temporal flexibility in response to resident requirements. The degree of proximity to all residents is determined by using a coverage radius that represents the maximum distance residents need to travel to access a recycling point. The temporal flexibility is assessed by the availability of proximal recycling points at times suitable to the lifestyles of all residents concerned. In Taiwan, the MSW collection is implemented at fixed locations and at fixed times. Residents must deposit their garbage directly into the collection vehicle. To facilitate the assignment of collection vehicles and to encourage residents to thoroughly separate their recyclables, in Taiwan MSW and recyclable materials are usually collected at the same time by different vehicles. A heuristic procedure including an integer programming (IP) model and ant colony optimization (ACO) is explored in this study to determine an efficient two-shift collection plan that takes into account RAC factors. The IP model has been developed to determine convenient collection points in each shift on the basis of proximity, and then the ACO algorithm is applied to determine the most effective routing plan of each shift. With the use of a case study involving a city in Taiwan, this study has demonstrated that collection plans generated using the above procedure are superior to current collection plans on the basis of proximity and total collection distance.