In Malaysia, the rapid growth of population and new consumption trends are causing an increase in municipal solid waste (MSW) generation rate. To make matters worse, the current MSW handling practices in Malaysia are mostly dumping in open landfills with no proper landfill gas collection and energy recovery system, producing greenhouse gas (GHG) emissions to the atmosphere. This handling process undoubtedly causes climate change and is economically unfavourable. In this study, a multi-objective mixed-integer linear programming (MILP) approach was simulated using General Algebraic Modeling System (GAMS) to determine the optimum allocation of MSW on different disposal and treatment facilities (DTF), including sanitary landfills, incineration, recycling, anaerobic digestion, composting, and plasma arc gasification. The mathematical model utilised the augmented e-constraint method to minimise the capital and operational cost, maximise the value of final products, and minimise GHG emissions simultaneously. As compared to the current MSW management situation in Malaysia (total cost: 7.24 M MYR/d, net GHG emissions: 70,465 t CO2-eq/d), the least cost Pareto solution (total cost: 7.23 M MYR/d, net GHG emissions: 24,630 t CO2-eq/d) shows a more than 65 % reduction in GHG emissions without incurring any additional cost. The 9th,10th, and 11th Pareto optimal solutions would be able to achieve the national recycling target of 22 % by 2020 as promulgated by the Malaysia Government. It is hoped that this study can provide guidance on the best allocation of MSW on DTF for decision-makers to plan and design the best in class solution for MSW management not only in Malaysia but also regions that face a similar MSW disposal dilemma.