Global AI and Data Science

Transport Optimization for Chemical Products – Minimum Cost Network Flow Optimization Problem
A chemical manufacturing company is tasked with transporting 190 tonnes of chemical products from four storage depots (D1, D2, D3, and D4) to three recycling centers (C1, C2, and C3).
•
Depot D1 holds 50 tonnes,
•
Depot D2 holds 40 tonnes,
•
Depot D3 holds 35 tonnes, and
•
Depot D4 holds 65 tonnes.
We assume that recycling centers do not have capacity restrictions. The company aims to transport these products using two available modes of transport: road and rail. The transportation cost per tonne varies depending on the mode of transport and the depot-recycling center route:
•
Depot D1 delivers to C1 and C2 by road at a cost of €12/t and €11/t, respectively.
•
Depot D2 delivers to C1 by rail (€12/t) or road (€14/t).
•
Depot D3 delivers to C2 by road (€9/t), and to C3 by rail (€10/t) or road (€5/t).
•
Depot D4 delivers to C2 by rail (€11/t) or road (€14/t), and to C3 by rail (€10/t) or road (€14/t).
In addition, the contract with the railway company requires that each rail shipment must carry at least 10 tonnes but not exceed 50 tonnes. There are no such constraints for road transport.
Your task as an Operational Research Analyst for the company is to formulate an optimization model that will minimize the total transportation cost while ensuring all 190 tonnes are transported. You should:
a.
Draw a network diagram that represents the problem.
b.
Write a mathematical formulation for the problem.
i)
Define the decision variables clearly.
ii)
State the objective function and explain the company's goal.
iii)
Identify the constraints including transport mode capacities, depot storage, and rail shipment requirements.
c.
Once the model (mathematical formulation) is formulated, you will implement it in OPL (Optimization Programming Language), solve the problem, and present your results, including the total transportation cost and the transport plan for each route.
Hint: You need to first draw the network of the problem with all possible connections from depots to recycling centers considering alternative modes of transportation (road and rail). In addition to nodes that represent depots and recycling centers, you may consider creating intermediate dummy nodes of "road" and "rail" for each recycling center. These dummy nodes will be connecting to recycling centers and they will be connected from depots based on the descriptions and limitations presented in the problem. Finally, add a dummy demand node (sink node) that each recycling center connects to by artificial arcs. You may also choose to include a dummy source node that connects to the depots via artificial arcs. Each arc in the network is defined by three parameters: minimum flow, maximum flow or capacity, and cost.

Hi Jamshed,

Thanks for your contribution to the Community. The formating of your blog is a bit off with the bullets. 

Could you expand on the title of your blog so that it provides more clarity on the contents please. 

Thanks,

Nick

Transport Optimization for Chemical Products – Minimum Cost Network Flow Optimization Problem
A chemical manufacturing company is tasked with transporting 190 tonnes of chemical products from four storage depots (D1, D2, D3, and D4) to three recycling centers (C1, C2, and C3).
•
Depot D1 holds 50 tonnes,
•
Depot D2 holds 40 tonnes,
•
Depot D3 holds 35 tonnes, and
•
Depot D4 holds 65 tonnes.
We assume that recycling centers do not have capacity restrictions. The company aims to transport these products using two available modes of transport: road and rail. The transportation cost per tonne varies depending on the mode of transport and the depot-recycling center route:
•
Depot D1 delivers to C1 and C2 by road at a cost of €12/t and €11/t, respectively.
•
Depot D2 delivers to C1 by rail (€12/t) or road (€14/t).
•
Depot D3 delivers to C2 by road (€9/t), and to C3 by rail (€10/t) or road (€5/t).
•
Depot D4 delivers to C2 by rail (€11/t) or road (€14/t), and to C3 by rail (€10/t) or road (€14/t).
In addition, the contract with the railway company requires that each rail shipment must carry at least 10 tonnes but not exceed 50 tonnes. There are no such constraints for road transport.
Your task as an Operational Research Analyst for the company is to formulate an optimization model that will minimize the total transportation cost while ensuring all 190 tonnes are transported. You should:
a.
Draw a network diagram that represents the problem.
b.
Write a mathematical formulation for the problem.
i)
Define the decision variables clearly.
ii)
State the objective function and explain the company's goal.
iii)
Identify the constraints including transport mode capacities, depot storage, and rail shipment requirements.
c.
Once the model (mathematical formulation) is formulated, you will implement it in OPL (Optimization Programming Language), solve the problem, and present your results, including the total transportation cost and the transport plan for each route.
Hint: You need to first draw the network of the problem with all possible connections from depots to recycling centers considering alternative modes of transportation (road and rail). In addition to nodes that represent depots and recycling centers, you may consider creating intermediate dummy nodes of "road" and "rail" for each recycling center. These dummy nodes will be connecting to recycling centers and they will be connected from depots based on the descriptions and limitations presented in the problem. Finally, add a dummy demand node (sink node) that each recycling center connects to by artificial arcs. You may also choose to include a dummy source node that connects to the depots via artificial arcs. Each arc in the network is defined by three parameters: minimum flow, maximum flow or capacity, and cost.

Transport Optimization for Chemical Products – Minimum Cost Network Flow Optimization Problem
A chemical manufacturing company is tasked with transporting 190 tonnes of chemical products from four storage depots (D1, D2, D3, and D4) to three recycling centers (C1, C2, and C3).
•
Depot D1 holds 50 tonnes,
•
Depot D2 holds 40 tonnes,
•
Depot D3 holds 35 tonnes, and
•
Depot D4 holds 65 tonnes.
We assume that recycling centers do not have capacity restrictions. The company aims to transport these products using two available modes of transport: road and rail. The transportation cost per tonne varies depending on the mode of transport and the depot-recycling center route:
•
Depot D1 delivers to C1 and C2 by road at a cost of €12/t and €11/t, respectively.
•
Depot D2 delivers to C1 by rail (€12/t) or road (€14/t).
•
Depot D3 delivers to C2 by road (€9/t), and to C3 by rail (€10/t) or road (€5/t).
•
Depot D4 delivers to C2 by rail (€11/t) or road (€14/t), and to C3 by rail (€10/t) or road (€14/t).
In addition, the contract with the railway company requires that each rail shipment must carry at least 10 tonnes but not exceed 50 tonnes. There are no such constraints for road transport.
Your task as an Operational Research Analyst for the company is to formulate an optimization model that will minimize the total transportation cost while ensuring all 190 tonnes are transported. You should:
a.
Draw a network diagram that represents the problem.
b.
Write a mathematical formulation for the problem.
i)
Define the decision variables clearly.
ii)
State the objective function and explain the company's goal.
iii)
Identify the constraints including transport mode capacities, depot storage, and rail shipment requirements.
c.
Once the model (mathematical formulation) is formulated, you will implement it in OPL (Optimization Programming Language), solve the problem, and present your results, including the total transportation cost and the transport plan for each route.
Hint: You need to first draw the network of the problem with all possible connections from depots to recycling centers considering alternative modes of transportation (road and rail). In addition to nodes that represent depots and recycling centers, you may consider creating intermediate dummy nodes of "road" and "rail" for each recycling center. These dummy nodes will be connecting to recycling centers and they will be connected from depots based on the descriptions and limitations presented in the problem. Finally, add a dummy demand node (sink node) that each recycling center connects to by artificial arcs. You may also choose to include a dummy source node that connects to the depots via artificial arcs. Each arc in the network is defined by three parameters: minimum flow, maximum flow or capacity, and cost.

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Jamshed Alam
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