A study on recycling model based on robust optimization

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The recycling industries face significant uncertainty in quantity of collected used products. Some studies point out variation of collection amount and such uncertainties create disincentives for recycling. We propose a recycler model of small size home electrical appliance with uncertainty in the amount of collection and examine the performance of robust optimzation. We confirmed that applying robust optimization increases average profit of recycler.Next, we focused on the possibility that a recycler with more advanced technology will be less likely to be assigned a contract in auction, because their bid will reflect its high fixed cost. We propose an auction model and showed that if a recycler has advanced technology with high fixed cost they will be less likely to be assigned a contract. We proposed a new mechanism based on robust optimization and showed that the proposed mechanism increases the possibility that a recycler with advanced technology will be assigned a contract.