A review of mathematical optimization models applied to the sugarcane supply chain

2021 ◽  
Author(s):  
Eduardo dos Santos Teixeira ◽  
Socorro Rangel ◽  
Helenice de O. Florentino ◽  
Silvio Alexandre de Araujo
Keyword(s):  
Supply Chain ◽  
Mathematical Optimization ◽  
Optimization Models

Experiences in Modeling, Simulation, and Optimization of Chemical Industry Supply Chains

Manufacturing ◽  
2002 ◽  
Author(s):  
Charles R. Standridge ◽  
David R. Heltne
Keyword(s):  
Supply Chain ◽  
Simulation Model ◽  
Production Planning ◽  
Simulation Optimization ◽  
Process Industry ◽  
Plant Production ◽  
Optimization Models ◽  
Individual Plant ◽  
Simulation And Optimization ◽  
Combined Simulation

We have developed and applied simulation as well as combined simulation – optimization models to represent process industry plant logistics and supply chain operations. The simulation model represents plant production, inventory, and shipping operations as well as inter-plant shipments. When a combined simulation-optimization approach is used, the simulation periodically invokes a classical production planning optimization model to set production and shipping levels. These levels are retrieved by and used in the simulation model. Process industry supply chain operations include stochastic elements such as customer demands whose expected values may vary in time as well as transportation lead times. The complexity of individual plant operations and logistics must be considered. Simulation provides the methods needed to integrate these elements in a single model. Periodically during a simulation run, production planning decisions that require optimization models may be made. Simulation experimental results are used to determine service levels to end customers as well as to set rail fleet sizes, inventory capacities, and capital equipment requirements for logistics as well as to assess alternative shipping schedules.

Profit Maximizing Network Modeling With Inventory and Capacity Considerations

2018 ◽  
pp. 5503-5515
Author(s):  
Tan Miller ◽  
Renato de Matta
Keyword(s):  
Supply Chain ◽  
Network Modeling ◽  
Demand Management ◽  
Global Supply Chain ◽  
Optimization Models ◽  
Business Decisions ◽  
Supply Chain Networks ◽  
Strategic Trade ◽  
Trade Offs ◽  
Production Distribution

Developing integrated strategic, tactical and operational manufacturing and distribution plans for the global supply chain of a large, international firm represents a formidable planning, as well as organizational undertaking. Moreover, to develop and execute plans that are not only integrated, but which maximize profits on a global basis presents a challenge of far greater magnitude. The use of advanced optimization modeling based analytics can generate keen insights for management decisions regarding sourcing, production, distribution, inventory and demand management on supply chain networks. This includes scenario and contingency planning analyses of complex strategic trade-offs such as the optimal balance between inventory levels and reserve manufacturing capacity on a network. In this chapter, we illustrate how optimization models can support a firm's planning efforts for these and related supply chain business decisions.

scholarly journals Combined Use of Mathematical Optimization and Design of Experiments for the Maximization of Profit in a Four-Echelon Supply Chain

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-25 ◽  
Author(s):  
Daniel Arturo Olivares Vera ◽  
Elias Olivares-Benitez ◽  
Eleazar Puente Rivera ◽  
Mónica López-Campos ◽  
Pablo A. Miranda
Keyword(s):  
Supply Chain ◽  
Design Of Experiments ◽  
Mathematical Optimization ◽  
Fractional Factorial ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Cost Component ◽  
Allocation Model

This paper develops a location-allocation model to optimize a four-echelon supply chain network, addressing manufacturing and distribution centers location, supplier selection and flow allocation for raw materials from suppliers to manufacturers, and finished products for end customers, while searching for system profit maximization. A fractional-factorial design of experiments is performed to analyze the effects of capacity, quality, delivery time, and interest rate on profit and system performance. The model is formulated as a mixed-integer linear programming problem and solved by using well-known commercial software. The usage of factorial experiments combined with mathematical optimization is a novel approach to address supply chain network design problems. The application of the proposed model to a case study shows that this combination of techniques yields satisfying results in terms of both its behavior and the obtained managerial insights. An ANOVA analysis is executed to quantify the effects of each factor and their interactions. In the analyzed case study, the transportation cost is the most relevant cost component, and the most relevant opportunity for profit improvement is found in the factor of quality. The proposed combination of methods can be adapted to different problems and industries.

Mathematical optimization of a supply chain for the production of fuel pellets from residual biomass

2016 ◽  
Vol 19 (3) ◽  
pp. 721-734 ◽  
Author(s):  
Manuel Alejandro Méndez-Vázquez ◽  
Fernando Israel Gómez-Castro ◽  
José María Ponce-Ortega ◽  
Alma Hortensia Serafín-Muñoz ◽  
José Ezequiel Santibañez-Aguilar ◽  
...  
Keyword(s):  
Supply Chain ◽  
Mathematical Optimization ◽  
Residual Biomass ◽  
Fuel Pellets
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