A multi-level multi-perspective reverse logistics model on e-waste

• Main Authors: Rapes, Andrew Kyle A., Padayao, Arvin Jerome A., Medida, Mary Antonette P.
• Format: text
• Language: English
• Published: Animo Repository 2018
• Subjects: Electronic waste; Industrial Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/7220
• Institution: De La Salle University

Due to the persistent operations of the informal waste sector in the Philippines, majority of the country's collected e-waste undergo resource recovery activities that are illegal and unregulated, which increases the possibility of releasing hazardous substances into the atmosphere. Given that existing research has come to a consensus that the informal waste sector of developing countries should be included in reverse logistics waste management networks, policies that govern the system should not only increase the overall recycling rates by diverting e-waste flows into the formal waste sector to improve their working conditions. This study addresses the need for multi-level, multi-perspective decision-making model that considers. convenience and accessibility of waste generators and informal collectors, respectively, as a function of time, the interests of stakeholders , and the health of waste sector constituents while simultaneously diverting the flow of e-waste towards through the use of an incentive system provided by the formal waste sector. The overall aim is to determine the optimal combinations of the e-waste sector entities to successfully motivate them in selling their e-waste to the formal sector. The convenience factor of waste generators and accessibility factor for informal collectors are modeled as a logarithmic function of retrieval time for waste sectors while the health risk of the informal recycler's constituents is modeled as an exponential growth function. The model was solved using goal programming and a modified epsilon constraint method to consider the contradicting objectives of the two sectors and underwent a sensitivity analysis using GAMS as solver.