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.

scholarly journals Optimal Supply Chain Network with Multi-Echelon

2019 ◽  
Vol 7 (2) ◽  
pp. 102-115
Author(s):  
Zaher Hamad Alsalem ◽  
Ramkumar Harikrishnakumar ◽  
Vatsal Maru ◽  
Krishna Krishnan
Keyword(s):  
Supply Chain ◽  
Supply Chain Design ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Objective Functions ◽  
Distribution Centers ◽  
Single Product ◽  
Study Objective ◽  
Total Cost ◽  
Customer Service Level

The study of the effect of redistribution strategy and aggregation, on a multi-echelon supply chain network by managing demand volatility is discussed in this research. For this an operational supply chain design is considered. Multi-echelon network consisting of manufacturing plants, distribution centers, warehouses, and retailers is used to develop the case study. Aggregation strategy was analyzed in the context of single product and multi-product for a multi-period production problem under demand uncertainty. Product sourcing between echelons and distribution strategies are considered for the study. Objective was to use the redistribution strategy to optimize the objective functions for the network. The objective functions include minimization of total cost, minimization of overage and stock-out conditions, and maximization of the customer service level. The total cost function includes product flow, transportation cost and distance cost. The mathematical formulation is carried out in Mixed Integer Linear Programming (MILP) with the help of Generic Algebraic Modeling System (GAMS). Problem formulation considers three type of demand based on volatility and uncertainty cases as high, medium, and low. The research is divided into three main phases to discuss an optimal multi-echelon supply chain network for single product using aggregation strategy.

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 A Multi-objective MILP Model Proposed to Optimize a Supply Chain Network for Microalgae-based Biofuels and Co-products: A Case Study in Iran

2021 ◽  
Author(s):  
Mohammad Ehsan Zerafati ◽  
Ali Bozorgi-Amiri ◽  
Amir-Mohammad Golmohammadi ◽  
Fariborz Jolai
Keyword(s):  
Supply Chain ◽  
Objective Function ◽  
Environmental Impacts ◽  
Deterministic Model ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Multi Objective ◽  
Proposed Model ◽  
Milp Model

Abstract Recently, due to the efficiency of cultivating microalgae, researchers and investors have paid considerable attention to the production of different biofuel products that are environmentally friendly. In this study, a two-stage deterministic model is proposed to design a microalgae-based biofuels and co-products supply chain network (MBCSCN). In the first stage, the appropriate locations for the cultivation of microalgae are identified through the analytical hierarchy process (AHP). In the second stage, a deterministic mathematical mixed integer linear programing (MILP) model is developed for a period of five years based on the criteria of economic and environmental impacts. The economic objective function maximizes the overall profit, while the environmental impacts objective function seeks to minimize the consumed fossil fuel throughout the supply chain. Then, a multi-objective MILP optimization problem is solved using the ε-constraint method. The proposed model is evaluated through a case study in Iran. It has helped to identify appropriate locations for the cultivation of microalgae and to specify the required quantity of feedstock, the species of microalgae, the required technology, and the transportation modes in each step of the supply chain.

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.

Choosing a Distribution Center to Improve the Vietnamese Fruit and Vegetable Supply Chain by the Hybrid Applied Mathematical Optimization and SAW

2020 ◽  
Author(s):  
Kieu Phan ◽  
Phong Ho
Keyword(s):  
Supply Chain ◽  
Survey Methods ◽  
Mathematical Optimization ◽  
Mekong Delta ◽  
Secondary Data ◽  
Distribution Center ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Fruit And Vegetable ◽  
Simple Additive Weighting

Abstract In the current market economic conditions, the distribution center plays an important role in the the supply chain’s operation, especially when the fruit and vegetable supply chains in Vietnam still do not have a suitable distribution center, leading to high arrival costs and slow shipping times. Therefore, researching and proposing a model to locate distribution centers, contributing to cost reduction of the fruit and vegetable supply chain is a crucial issue in Vietnam today. Therefore, using many survey methods such as in-depth interview, focus groups, face-to-face to collect a total of 439 samples in Vinh Long province, as well as secondary data from new articles, studies, research articles, other authentic sources directing the administration of provincial statistical management and yearbooks for analyzing the sweet potato supply chain in Vinh Long province of the Mekong Delta region. First, this study used mixed-integer linear programming and compromised programming based on IBM CPLEX Optimizer to choose a distribution center when trading-off between cost and transport time. Secondly, Simple Additive Weighting (SAW) for decision support based on excel software from the results of experts’ answering to increase the objectivity for determining the location of the Distribution Center as well as in accordance with both the actual situation and the comprehensive development of local socio-economy. The contribution of proposing the mathematical model is to choose a suitable place for saving costs and reducing transport times. In additon, this approach method could be applied to other Vietnamese agri-fresh products for upgrading the competitiveness, compared with other countries' agricultural products in terms of price and quality so far.

scholarly journals A stochastic location and allocation model for critical items to response large-scale emergencies: A case of Turkey

2016 ◽  
Vol 7 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Erkan Celik ◽  
Nezir Aydin ◽  
Alev Taskin Gumus
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Allocation Model ◽  
Proposed Model ◽  
Stochastic Mixed Integer Programming ◽  
Stochastic Location ◽  
Relief Organizations

This paper aims to decide on the number of facilities and their locations, procurement for pre and post-disaster, and allocation to mitigate the effects of large-scale emergencies. A two-stage stochastic mixed integer programming model is proposed that combines facility location- prepositioning, decisions on pre-stocking levels for emergency supplies, and allocation of located distribution centers (DCs) to affected locations and distribution of those supplies to several demand locations after large-scale emergencies with uncertainty in demand. Also, the use of the model is demonstrated through a case study for prepositioning of supplies in probable large-scale emergencies in the eastern and southeastern Anatolian sides of Turkey. The results provide a framework for relief organizations to determine the location and number of DCs in different settings, by using the proposed model considering the main parameters, as; capacity of facilities, probability of being affected for each demand points, severity of events, maximum distance between a demand point and distribution center. 

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