In this study, an inexact minimax regret mixed integer programming (IMMRIP) method is applied to long-term planning of municipal solid waste (MSW) management in the City of Regina. The method can help tackle the dynamic, interactive, and uncertain characteristics of the solid waste management system in the city, and can address issues concerning plans for cost-effective waste diversion and landfill prolongation. Thirty-six situations were examined based on multiple alternatives and scenarios under different waste-generation levels. Reasonable solutions have been generated for decisions of system-capacity expansion and waste-flow allocation, demonstrating complex tradeoffs among system cost, regret level, and constraint-violation risk. Solutions associated with further inexact minimax regret (IMMR) analyses can help tackle tradeoffs between minimized system cost and maximized system feasibility. Under the optimal alternative, the system would reach a maximum reliability with the lowest risks of penalty and wastage. Results provide valuable inputs for adjustment of the existing waste flow allocation patterns to satisfy the city's diversion goals, long-term capacity planning for the city's waste management system, and generation desired policies for managing the city's waste collection and treatment.