Dynamic waste management (DWM): towards an evolutionary decision-making approach

Area of Science:

• Environmental Engineering
• Operations Research
• Sustainable Systems

Background:

• Current waste management systems face challenges in maintaining consistent flow to treatment facilities.
• Dynamic adjustments are needed to balance incoming waste loads with treatment capacities.

Purpose of the Study:

• To introduce and demonstrate the Dynamic Waste Management (DWM) approach for sustainable and efficient waste processing.
• To provide a decision-making framework for optimizing waste treatment processes, locations, and transport.

Main Methods:

• Developed the Dynamic Waste Management (DWM) approach based on the law of conservation of energy.
• Introduced prioritization index (PI) for waste generators and a global allocation index for treatment processes.
• Incorporated linear index load loss (ΔH) for waste transport and utilized reserve (stock) for temporary storage.

Main Results:

• Demonstrated dynamic distribution of variable monthly waste to priority treatment processes.
• Showcased how reserve capacity eases network load and ensures constant feeding of treatment facilities.
• Validated DWM's effectiveness in a case study with three waste sources.

Conclusions:

• The DWM approach offers a sustainable and evolutionary solution for dynamic waste management.
• It serves as a valuable decision-making tool for evaluating and optimizing waste treatment infrastructure and logistics.
• Effective utilization of reserves enhances network stability and process efficiency.