scholarly journals A Propose Model Optimal Supply Chain Distribution Network for Farmer Industrial

2020 ◽  
Vol 3 (2) ◽  
pp. 43-53
Author(s):  
Ammar Salamh Mujali Al-Rawahna ◽  
Anas Yahya Bader Al Hadid
Keyword(s):  
Supply Chain ◽  
Network Flows ◽  
Programming Model ◽  
Cost Minimization ◽  
Distribution Network ◽  
Distribution Networks ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Supply Chain System ◽  
External Interface

A supply chain should be operated in the most efficient way in a highly competitive environment, with the goals of cost minimization, shipment delays, inventories and expenditures, and distribution maximization, gain, return on investment, level of customer support, and efficiency. The development of supply-chain distribution networks is therefore an extremely complex task, due to the large physical production and distribution network flows, the uncertainties associated with external interface customers and suppliers as well as the non-linear dynamics linked to internal information flows. This study aims to address a problem in domestic distribution in a supply chain system that includes manufacturers, distribution centers and consumer zones to determine the optimum configuration of the network. We propose a mixed integer linear programming model to solve the problem.

scholarly journals Supply chain optimization with variable demand by considering financial criteria and scenarios

2017 ◽  
Vol 26 (44) ◽  
pp. 21 ◽  
Author(s):  
John Willmer Escobar
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Net Present Value ◽  
Programming Model ◽  
Supply Chain Design ◽  
Mixed Integer ◽  
Supply Network ◽  
Distribution Centers ◽  
Supply Chain Optimization ◽  
Starting Point

This paper contemplates the supply chain design problem of a large-scale company by considering the maximization of the Net Present Value. In particular, the variability of the demand for each type of product at each customer zone has been estimated. As starting point, this paper considers an established supply chain for which the main problem is to determine the decisions regarding expansion of distribution centers. The problem is solved by using a mixed-integer linear programming model, which optimizes the different demand scenarios. The proposed methodology uses a scheme of optimization based on the generation of multiple demand scenarios of the supply network. The model is based on a real case taken from a multinational food company, which supplies to the Colombian and some international markets. The obtained results were compared with the equivalent present costs minimization scheme of the supply network, and showed the importance and efficiency of the proposed approach as an alternative for the supply chain design with stochastic parameters.

Modeling of Green Supply Chain Logistics

2010 ◽  
pp. 268-282 ◽  
Author(s):  
Hsin-Wei Hsu
Keyword(s):  
Supply Chain ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Minimum Cost ◽  
Mixed Integer ◽  
Green Supply Chain ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Supply Chain Logistics ◽  
The Subject

The green supply chain management has drawn researchers’ attention in recent years, but most of the proposed models for green topics on the subject are case based, and for this reason, they lack generality. In this work, the design of a supply chain network is studied. In this chapter, we try to overcome this limitation and a generalized model is proposed, in which a logistics chain network problem is formulated into a 0-1 mixed integer linear programming model and the decisions for the function of manufactures, distribution centers, and dismantlers will be suggested with minimum cost. A numerical example is provided for illustration.

Modeling of Green Supply Chain Logistics

2011 ◽  
pp. 327-341
Author(s):  
Hsin-Wei Hsu
Keyword(s):  
Supply Chain ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Minimum Cost ◽  
Mixed Integer ◽  
Green Supply Chain ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Supply Chain Logistics ◽  
The Subject

The green supply chain management has drawn researchers’ attention in recent years, but most of the proposed models for green topics on the subject are case based, and for this reason, they lack generality. In this work, the design of a supply chain network is studied. In this chapter, we try to overcome this limitation and a generalized model is proposed, in which a logistics chain network problem is formulated into a 0-1 mixed integer linear programming model and the decisions for the function of manufactures, distribution centers, and dismantlers will be suggested with minimum cost. A numerical example is provided for illustration.

scholarly journals Design of a Distribution Network Using Primal-Dual Decomposition

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
J. A. Marmolejo ◽  
R. Rodríguez ◽  
O. Cruz-Mejia ◽  
J. Saucedo
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Distribution Network ◽  
Mixed Integer ◽  
Direct Solution ◽  
Distribution Centers ◽  
Dual Decomposition ◽  
Primal Dual ◽  
Cross Decomposition ◽  
Primal And Dual

A method to solve the design of a distribution network for bottled drinks company is introduced. The distribution network proposed includes three stages: manufacturing centers, consolidation centers using cross-docking, and distribution centers. The problem is formulated using a mixed-integer programming model in the deterministic and single period contexts. Because the problem considers several elements in each stage, a direct solution is very complicated. For medium-to-large instances the problem falls into large scale. Based on that, a primal-dual decomposition known as cross decomposition is proposed in this paper. This approach allows exploring simultaneously the primal and dual subproblems of the original problem. A comparison of the direct solution with a mixed-integer lineal programming solver versus the cross decomposition is shown for several randomly generated instances. Results show the good performance of the method proposed.

The Optimization of Costs of Supply Chain Network

2015 ◽  
Vol 741 ◽  
pp. 801-805
Author(s):  
Zhuo Dai
Keyword(s):  
Supply Chain ◽  
Programming Model ◽  
Transportation Cost ◽  
Raw Material ◽  
Mixed Integer ◽  
Variable Cost ◽  
Fixed Cost ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Penalty Cost

This research proposes a muti-echelon supply chain network design model. The model includes raw material suppliers, manufacturers, distribution centers, and customer zones. The purpose of this research is to minimize the total costs of supply chain network. The total costs include transportation cost, fixed cost, variable cost, penalty cost. This model is a mixed integer linear programming model. In general, it is very difficult to solve the model. In order to solve the model, Cplex12.6 is used. The results show that this model can be solved by this mathematical programming software well.

The Design of Closed-Loop Supply Chain Network

2015 ◽  
Vol 744-746 ◽  
pp. 1910-1914
Author(s):  
Zhuo Dai
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Programming Model ◽  
Raw Material ◽  
Mixed Integer ◽  
Variable Cost ◽  
Fixed Cost ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Closed Loop Supply Chain

This paper designs a model of muti-echelon closed-loop supply chain network (CLSC network). CLSC network includes raw material suppliers, manufacturers, distribution centers, collection centers and customer zones. The purpose of this paper is to minimize the overall costs of CLSC network. The overall costs include transportation cost, fixed cost, variable cost, penalty cost. This model is a mixed integer linear programming model. In general, it is very difficult to solve the model. Cplex12.6 is used in order to deal with this model. The results show that this model can be solved by Cplex12.6 well.

scholarly journals A Dynamic Multi-Period, Mixed-Integer Linear Programming Model for Cost Minimization of a Three-Echelon, Multi-Site and Multi-Product Construction Supply Chain

Logistics ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 19
Author(s):  
Aspasia Koutsokosta ◽  
Stefanos Katsavounis
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Integer Linear Programming ◽  
Strategic Alliances ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Cost Minimization ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Integer Linear Programming Model

Quantifying the benefits of construction supply chain management through prescriptive models is a challenging and fast-growing research area that still lacks standardized optimization models with full integrative potential. In response to the needs and the peculiarities of the construction industry, this paper proposes an innovative model that merges temporal and project-based supply chains into a sustainable network with repetitive flows, large scope contracts, strategic alliances and economies of scale. It is a dynamic mixed-integer linear programming model for cost minimization of a three-echelon supply chain serving multiple sites with multiple products over a time horizon. Its novelty lies in yielding optimal decisions on network design, product quantities to be purchased and transported, shipments and inventory levels in all echelons under any logistics system in a multi-period, multi-product and multi-project environment with discount schemes and strategic preferences. The model is general enough to be implemented by any general contractor acting as a system integrator but also allows customization with logical constraints. All these features constitute an innovative, versatile and flexible managerial decision making tool. Model implementation is based on a spreadsheet optimization software and is followed by post-solution analysis, sensitivity analysis and multiple parameterized optimizations.

scholarly journals Design of a Logistics Nonlinear System for a Complex, Multiechelon, Supply Chain Network with Uncertain Demands

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Aaron Guerrero Campanur ◽  
Elias Olivares-Benitez ◽  
Pablo A. Miranda ◽  
Rodolfo Eleazar Perez-Loaiza ◽  
Jose Humberto Ablanedo-Rosas
Keyword(s):  
Supply Chain ◽  
Programming Model ◽  
Piecewise Linear ◽  
Distribution Network ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Piecewise Linear Approximation ◽  
Computational Time ◽  
Local Optimum ◽  
Decision Variables

Industrial systems, such as logistics and supply chain networks, are complex systems because they comprise a big number of interconnected actors and significant nonlinear and stochastic features. This paper analyzes a distribution network design problem for a four-echelon supply chain. The problem is represented as an inventory-location model with uncertain demand and a continuous review inventory policy. The decision variables include location at the intermediate levels and product flows between echelons. The related safety and cyclic inventory levels can be computed from these decision variables. The problem is formulated as a mixed integer nonlinear programming model to find the optimal design of the distribution network. A linearization of the nonlinear model based on a piecewise linear approximation is proposed. The objective function and nonlinear constraints are reformulated as linear formulations, transforming the original nonlinear problem into a mixed integer linear programming model. The proposed approach was tested in 50 instances to compare the nonlinear and linear formulations. The results prove that the proposed linearization outperforms the nonlinear formulation achieving convergence to a better local optimum with shorter computational time. This method provides flexibility to the decision-maker allowing the analysis of scenarios in a shorter time.

scholarly journals Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1452
Author(s):  
Cristian Mateo Castiblanco-Pérez ◽  
David Esteban Toro-Rodríguez ◽  
Oscar Danilo Montoya ◽  
Diego Armando Giral-Ramírez
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Power Balance ◽  
Continuous Version ◽  
Discrete Part

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

scholarly journals Efficient Operative Cost Reduction in Distribution Grids Considering the Optimal Placement and Sizing of D-STATCOMs Using a Discrete-Continuous VSA

2021 ◽  
Vol 11 (5) ◽  
pp. 2175
Author(s):  
Oscar Danilo Montoya ◽  
Walter Gil-González ◽  
Jesus C. Hernández
Keyword(s):  
Objective Function ◽  
Reactive Power ◽  
Programming Model ◽  
Search Algorithm ◽  
Solution Space ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Solution Vector ◽  
The Impact

The problem of reactive power compensation in electric distribution networks is addressed in this research paper from the point of view of the combinatorial optimization using a new discrete-continuous version of the vortex search algorithm (DCVSA). To explore and exploit the solution space, a discrete-continuous codification of the solution vector is proposed, where the discrete part determines the nodes where the distribution static compensator (D-STATCOM) will be installed, and the continuous part of the codification determines the optimal sizes of the D-STATCOMs. The main advantage of such codification is that the mixed-integer nonlinear programming model (MINLP) that represents the problem of optimal placement and sizing of the D-STATCOMs in distribution networks only requires a classical power flow method to evaluate the objective function, which implies that it can be implemented in any programming language. The objective function is the total costs of the grid power losses and the annualized investment costs in D-STATCOMs. In addition, to include the impact of the daily load variations, the active and reactive power demand curves are included in the optimization model. Numerical results in two radial test feeders with 33 and 69 buses demonstrate that the proposed DCVSA can solve the MINLP model with best results when compared with the MINLP solvers available in the GAMS software. All the simulations are implemented in MATLAB software using its programming environment.

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