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A M U LT I -OBJECT I VE OPT I M I ZAT I ON

F OR GREEN SU PPLY CH AI N N ET WORK D ESI GN Reviewed by

DANANG KISWORO / 10074073


I ntr oduction Operations in supply chain and logistics ar e par t of today’s most impor tant economic activities as they remain to be vital tools for businesses to remain competitive. T r anspor tation activities ar e significant sour ces of air pollution and gr eenhouse gas emissions, with the former known to have harmful effects on human health and the latter responsible for global warming. The researcher are motivated to study a “gr een� supply chain netw or k design pr oblem w her e an initial investment on envir onmental pr otection equipment or techniques should be deter mined in the design phase. This investment can influence the environmental indicators in operations phase.


L iter atur e Review According to the most recent comprehensive review on GrSCM by Srivastava (2007), tw o types of “gr eenness� ar e consider ed by r esear cher s: gr een design for pr oducts (Kuo et al. 2001) and gr een oper ations. The supply chain network design problem is usually modeled as a single objective pr oblem (Melkote and Daskin (2001) and Santoso et al. (2005)). M ulti-objective optimization is a w idely used in var iety of ar eas (Sabri and Beamon, 2000; MaxShen et al. 2005; Hu et al. 2009; Koksalan and Tuncer, 2009; Ou Yang et al. 2009). and is also used to embed into a multitude of decision suppor t system (Despotis and Derpanis 2008; Gao et al. 2009; Stummer et al. 2009).


M ethodology (1/7)

1.Problem Definition Supply Chain Network G =(N,A) N is the set of Nodes A is the set of Arcs N composed by the set of Suppliers S, facilities F and customer C N=S盞:盞, When given demand forecasting, we not only aim to choose the potential suppliers from suppliers set and decide which facility to open and finally consider how to distribute the product, but also consider the CO2 emission in each process of the whole network.


M ethodology (2/7)

2. Modeling Parameter : Parameter : Parameter : Parameter : Setup Cost for Facility Environmental j Investment in Transport Facility Handling j cost for product cost for pproduct from facility p in facility i to j j

Decision Variable Decision : Variable : Decision Variable : Decision Variable : 1, if facility j is open the environment protection level in j p from flowflow of facility product of product p from node node i to node i to node j j

Total Cost =

Fixed Setup Cost

+

Environmental Protection Investment

+

Total Transportation Cost

+

Handling Cost

Parameter : Parameter : CO2 emission in facility j for handling Environmental product Investment p in Facility j

Decision Variable : Decision Variable : flow of product p from node i to node thej environment protection level in facility j

Total CO2 Emission =

CO2 Emission in all Facilities

+

CO2 Emission from Supplier to facility and how to transport it


M ethodology (3/7)

2. Solving Approach Parameter : Parameter : Parameter : Transport cost for product Handling Setup p fromCost facility cost forifor Facility to product j j p in facility j

Decision Variable : Decision Variable : Decision Variable : 1,flow if ienvironment level is selected flow of product p from node toofnode product j pprotection from node i to lnode j

Total Cost =

Total Transportation Cost

+

Fixed Setup Cost

+

Handling Cost

Parameter : Fixed environmental investment and per unit Parameter : Environmental influence in facility j under lEnvironmental environmental Investment in Facility j level

Total CO2 Emission =

Decision Variable : Decision Variable : the environment protection level in facility j Amount of product p handling in facility j unt\der CO2 Emission from Supplier l environmental protection level

CO2 Emission in all Facilities

+

to facility and how to transport it


M ethodology (4/7)

Solving Approach It is well-known that there exist multiple nondominated solutions for a multi-objective optimization problem. Those solutions are called “Pareto optimal” solutions. In this paper, our objective is to obtain a “Pareto frontier” which provides evenly distributed Pareto solutions and it is convenient for decision maker to select a suitable configuration. In this paper, it is important to obtain a well distributed Pareto frontier as we are investigating how different parameters influence the decision making behavior and we are aim to provide an effective decision support tool for industry.


M ethodology (5/7)

3. Computational Experiments The problem is solved by the normalized normal constraint method and it is implemented by Microsoft Visual C++ 6.0, and each sub-problem is solved by ILOG CPLEX 9.0 solver subroutine. Consider the Six-node network shown. There are 3 Supplier and 2 product. Each arc is associated with transportation cost and an amount of CO2 Emission. The decision maker should determine: (1)Where to set up the facility ? (2)How to set environmental protection level ? (3) Which suppliers should be selected for each facility? (4) How products are transported ?


M ethodology (6/7) Scenario A : Set the max CO2 Emission 16600


M ethodology (7/7) Scenario B : Set the max CO2 Emission 12000


Result (1/3) I f the Capacity Ratio is incr ease, it w ill effect to decr ease Cost and CO2 Emission. Definition of Capacity ratio is network capacity over the total demand. Why larger capacity ratio exhibit lower total cost and lower CO2 Emission? Because when the demand increases, the network provides more flexibility to conduct logistic cost and CO2 Emission in Transportation Process.

Capacity Ratio = 1 ďƒ  Total Cost =7300, CO2 = 2300 Capacity Ratio = 1.2 ďƒ  Total Cost = 7000, CO2 = 2150


Result (2/3) I f the Supply Range is I ncr ease, it w ill effect to decr ease T otal Cost and CO2 Emission. Supply range means supplier range include the distance and the number of supplier. Why larger supply range exhibit lower total cost and lower CO2 Emission? Because if the company has close supplier and rich facilities, we can reduce C02 Emission and transportation cost. Facility X

X+2

Supplier

Facility

Supply Range = [1,1.2] ďƒ  Total Cost =7300, CO2 = 2310 Supply Range = [1.5,2] ďƒ  Total Cost = 7180, CO2 = 2280 Facility Supplier X

X-2 Facility

Supplier Aft er : Total Cost and CO2 Emission 2x-2 Befor e : Total Cost and CO2 Emission 2x+2


Result (3/3) I f the D emand is I ncr ease, it w ill not effect to decr ease CO2 Emission significantly. But if the Demand is increase, it will make greater profit, and this profit can consider to investing more in environmental protection such as purchase equipment or technology.


M ethodology (2/7)

2. Modeling Parameter : Parameter : Parameter : Parameter : Setup Cost for Facility Environmental j Investment in Transport Facility Handling j cost for product cost for pproduct from facility p in facility i to j j

Decision Variable Decision : Variable : Decision Variable : Decision Variable : 1, if facility j is open the environment protection level in j p from flowflow of facility product of product p from node node i to node i to node j j

Total Cost =

Fixed Setup Cost

+

Environmental Protection Investment

+

Total Transportation Cost

+

Handling Cost

Parameter : Parameter : CO2 emission in facility j for handling Environmental product Investment p in Facility j

Decision Variable : Decision Variable : flow of product p from node i to node thej environment protection level in facility j

Total CO2 Emission =

CO2 Emission in all Facilities

+

CO2 Emission from Supplier to facility and how to transport it


M ethodology (3/7)

2. Solving Approach Parameter : Parameter : Parameter : Transport cost for product Handling Setup p fromCost facility cost forifor Facility to product j j p in facility j

Decision Variable : Decision Variable : Decision Variable : 1,flow if ienvironment level is selected flow of product p from node toofnode product j pprotection from node i to lnode j

Total Cost =

Total Transportation Cost

+

Fixed Setup Cost

+

Handling Cost

Parameter : Parameter : CO2 emission in facility j for handling product Environmental p Investment in Facility j

Decision Variable : flow of product p from node i to node j

Total CO2 Emission =

CO2 Emission in all Facilities

+

Decision Variable : the environment protection level in facility j

CO2 Emission from Supplier to facility and how to transport it



A Multi-Objective Optimization for Green Supply Chain Network - SHE