27 An Economic Evaluation of Recycling System in Next-Generation …
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with the risk of a new recycling business. In this study, some scenarios are set up
and the knowledge to a future recycling business is given by evaluating risk and
economic efficiency for each scenario.
27.2 Literature Review
There are several ongoing studies that evaluate the future demand of REEs (Zhou
et al. 2017) and the current status of recycling (Yang et al. 2016; Du 2011). Moreover,
Artem investigated the flow of the rare earth supply chain around the world by
examining the production and supply of REEs (Golev et al. 2016). However, to make
the industry sustainable, it is necessary to evaluate the cost of Nd recycling from
EOL products with regard to the rapidly increasing quantities of waste. However, the
change in the future demand of REEs will affect the transportation cost that is incurred
while collecting the EOL waste. Therefore, in order to consider transportation costs,
a recycling system is built using location-routing problems (LRP) (Min et al. 1998).
The LRP is that minimizes the sum of the facility cost which is proportional to
the number of sites and the transportation cost which is proportional to the moving
distance when input data as collection volume. Therefore, in the LRP dealt with in
this research, instead of deciding the location of the facility, it is extended to the plan
to add the facility place at each period. In the location routing plan, the collection
volume is given at a single period, and the LRP is solved using this volume. On the
other hand, in the LRP in multi periods, different collection volumes are given at
each period. Therefore, it is necessary to consider the addition of facilities by solving
LRP through multi periods. Therefore, this research is planned by solving a simple
LRP using the result of solving the LRP for every single year. In order for companies
to sustain recycling business, it is important to secure profits. In addition, because the
project involving facilities requires a preparation period, it is necessary to evaluate
the total cost based on forecasts in the future and plan the establishment of recycling
facilities. In the recycling business, one of the means to reduce the total cost is the
optimization of the number of recycling facilities, the place of installation and the
collection route. This makes it possible to reduce transportation costs (Ballou 2001).
Barreto et al. Proposed a method to solve the problem by generating a traveling
route only by the location information of demand places excluding bases as the first
stage and inserting bases near the route in the second stage (Barreto et al. 2007). Yu
et al. proposed a search method for LRP using a one-dimensional vector consisting
of bases and demand points. Then, they proposed a method to easily generate a
neighborhood solution by simultaneously changing the setting of the base and the
traveling route of the demand place using a one-dimensional vector and finding the
best solution (Yu et al. 2010). Rosemary et al. Modelled a location routing problem
focusing on distance constraints when designing distribution system wiring (Berger
et al. 2007). Moreover, as multi-period LRP, Sung proposed a method to determine
the location of the electric station that supplies electricity to electric vehicles etc. in
Korea (Chung and Kwon 2015). Xim has designed a multi-period network system that
385
with the risk of a new recycling business. In this study, some scenarios are set up
and the knowledge to a future recycling business is given by evaluating risk and
economic efficiency for each scenario.
27.2 Literature Review
There are several ongoing studies that evaluate the future demand of REEs (Zhou
et al. 2017) and the current status of recycling (Yang et al. 2016; Du 2011). Moreover,
Artem investigated the flow of the rare earth supply chain around the world by
examining the production and supply of REEs (Golev et al. 2016). However, to make
the industry sustainable, it is necessary to evaluate the cost of Nd recycling from
EOL products with regard to the rapidly increasing quantities of waste. However, the
change in the future demand of REEs will affect the transportation cost that is incurred
while collecting the EOL waste. Therefore, in order to consider transportation costs,
a recycling system is built using location-routing problems (LRP) (Min et al. 1998).
The LRP is that minimizes the sum of the facility cost which is proportional to
the number of sites and the transportation cost which is proportional to the moving
distance when input data as collection volume. Therefore, in the LRP dealt with in
this research, instead of deciding the location of the facility, it is extended to the plan
to add the facility place at each period. In the location routing plan, the collection
volume is given at a single period, and the LRP is solved using this volume. On the
other hand, in the LRP in multi periods, different collection volumes are given at
each period. Therefore, it is necessary to consider the addition of facilities by solving
LRP through multi periods. Therefore, this research is planned by solving a simple
LRP using the result of solving the LRP for every single year. In order for companies
to sustain recycling business, it is important to secure profits. In addition, because the
project involving facilities requires a preparation period, it is necessary to evaluate
the total cost based on forecasts in the future and plan the establishment of recycling
facilities. In the recycling business, one of the means to reduce the total cost is the
optimization of the number of recycling facilities, the place of installation and the
collection route. This makes it possible to reduce transportation costs (Ballou 2001).
Barreto et al. Proposed a method to solve the problem by generating a traveling
route only by the location information of demand places excluding bases as the first
stage and inserting bases near the route in the second stage (Barreto et al. 2007). Yu
et al. proposed a search method for LRP using a one-dimensional vector consisting
of bases and demand points. Then, they proposed a method to easily generate a
neighborhood solution by simultaneously changing the setting of the base and the
traveling route of the demand place using a one-dimensional vector and finding the
best solution (Yu et al. 2010). Rosemary et al. Modelled a location routing problem
focusing on distance constraints when designing distribution system wiring (Berger
et al. 2007). Moreover, as multi-period LRP, Sung proposed a method to determine
the location of the electric station that supplies electricity to electric vehicles etc. in
Korea (Chung and Kwon 2015). Xim has designed a multi-period network system that