scholarly journals Designing a Supply Chain Network under the Risk of Disruptions

2012 ◽  
Vol 2012 ◽  
pp. 1-23 ◽  
Author(s):  
Armin Jabbarzadeh ◽  
Seyed Gholamreza Jalali Naini ◽  
Hamid Davoudpour ◽  
Nader Azad
Keyword(s):  
Supply Chain ◽  
Supply Chain Design ◽  
Mixed Integer ◽  
Nonlinear Program ◽  
Supply Chain Network ◽  
Large Problem ◽  
Solution Methods ◽  
Total Profit ◽  
Order Quantities ◽  
Problem Instances

This paper studies a supply chain design problem with the risk of disruptions at facilities. At any point of time, the facilities are subject to various types of disruptions caused by natural disasters, man-made defections, and equipment breakdowns. We formulate the problem as a mixed-integer nonlinear program which maximizes the total profit for the whole system. The model simultaneously determines the number and location of facilities, the subset of customers to serve, the assignment of customers to facilities, and the cycle-order quantities at facilities. In order to obtain near-optimal solutions with reasonable computational requirements for large problem instances, two solution methods based on Lagrangian relaxation and genetic algorithm are developed. The effectiveness of the proposed solution approaches is shown using numerical experiments. The computational results, in addition, demonstrate that the benefits of considering disruptions in the supply chain design model can be significant.

scholarly journals Hybrid Electromagnetism-Like Algorithm for Dynamic Supply Chain Network Design under Traffic Congestion and Uncertainty

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Javid Jouzdani ◽  
Mohammad Fathian
Keyword(s):  
Supply Chain ◽  
Traffic Congestion ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Business Climate ◽  
Time Value Of Money ◽  
Solution Methods ◽  
Minlp Model ◽  
Minlp Problem ◽  
Conventional Solution

With the constantly increasing pressure of the competitive environment, supply chain (SC) decision makers are forced to consider several aspects of business climate. More specifically, they should take into account the endogenous features (e.g., available means of transportation, and the variety of products) and exogenous criteria (e.g., the environmental uncertainty, and transportation system conditions). In this paper, a mixed integer nonlinear programming (MINLP) model for dynamic design of a supply chain network is proposed. In this model, multiple products and multiple transportation modes, the time value of money, traffic congestion, and both supply-side and demand-side uncertainties are considered. Due to the complexity of such models, conventional solution methods are not applicable; therefore, two hybrid Electromagnetism-Like Algorithms (EMA) are designed and discussed for tackling the problem. The numerical results show the applicability of the proposed model and the capabilities of the solution approaches to the MINLP problem.

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.

scholarly journals Designing a clothing supply chain network considering pricing and demand sensitivity to discounts and advertisement

2020 ◽  
Author(s):  
Mohammad Mahdi Paydar ◽  
Marjan Olfati ◽  
chefi Triki
Keyword(s):  
Supply Chain ◽  
Programming Model ◽  
Rapid Development ◽  
Supply And Demand ◽  
Clothing Industry ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Total Profit ◽  
Demand Sensitivity

These days, clothing companies are becoming more and more developed around the world. Due to the rapid development of these companies, designing an efficient clothing supply chain network can be highly beneficial, especially with the remarkable increase in demand and uncertainties in both supply and demand. In this study, a bi-objective stochastic mixed-integer linear programming model is proposed for designing the supply chain of the clothing industry. The first objective function maximizes total profit and the second one minimizes downside risk. In the presented network, the initial demand and price are uncertain and are incorporated into the model through a set of scenarios. To solve the bi-objective model, weighted normalized goal programming is applied. Besides, a real case study for the clothing industry in Iran is proposed to validate the presented model and developed method. The obtained results showed the validity and efficiency of the current study. Also, sensitivity analyses are conducted to evaluate the effect of several important parameters, such as discount and advertisement, on the supply chain .  The results indicate that considering the optimal amount for discount parameter can conceivably enhance total profit by about 20% compared to the time without this discount scheme. When we take the optimized parameter into account for advertisement, 12% is obtained for the total profit. Based on our findings, the more the expected profit value, the higher the total amount of total profit and risk.  The results of this research also provide some interesting managerial insights for managers.

Supply Chain Design Including Quality Considerations

2014 ◽  
pp. 102-140 ◽  
Author(s):  
Krystel K. Castillo-Villar ◽  
Neale R. Smith
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Simulated Annealing ◽  
Network Design ◽  
Parameter Tuning ◽  
Supply Chain Design ◽  
Background Information ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Solution Methods

This chapter introduces the reader to Supply Chain Network Design (SCND) models that include the Cost Of Quality (COQ) among the relevant costs. In contrast to earlier models, the COQ is computed internally as a function of decisions taken as part of the design of the supply chain. Earlier models assume exogenously given COQ functions. Background information is provided on previous COQ modeling and on supply chain network design models. The authors’ COQ modeling is described in detail as is the SCND model that incorporates COQ. The COQ modeling includes prevention, appraisal, and both internal and external failure costs. Solution methods based on metaheuristics such as simulated annealing and the genetic algorithm are provided, including details on parameter tuning and computational testing. A genetic algorithm was found to yield the best results, followed by the simulated annealing approach. Topics for further research are provided as well as an extensive list of references for further reading.

scholarly journals Optimization of integrated supply chain network problem using hybrid genetic algorithm approach

2017 ◽  
Vol 7 (1.1) ◽  
pp. 1
Author(s):  
Anudari Chuluunsukh ◽  
Xing Chen ◽  
YoungSu Yun
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Integer Programming ◽  
Reverse Logistics ◽  
Hybrid Genetic Algorithm ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Total Profit ◽  
Genetic Algorithm Approach ◽  
Integrated Supply Chain

In this paper, an integrated supply chain network (ISCN) problem is designed. The ISCN problem is composed of forward and reverse logistics and represented by a nonlinear mixed integer programming (NMIP). The objective of the ISCN problem is to maximize the total profit which is consisted of total revenues and total costs resulting from its implementation. A hybrid genetic algorithm (HGA) approach proposed in this paper is applied to solve the NMIP. In numerical experiment, five scales of the ISCN problem are presented and they are solved using the proposed HGA approach and some conventional approaches. Experimental results show that the proposed HGA approach outperforms the others.

scholarly journals A multi-objective approach under uncertainty for designing a green meat supply chain network

2021 ◽  
Author(s):  
Fatemeh Mohebalizadehgashti
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Mixed Integer ◽  
Environmental Concerns ◽  
Supply Chain Network ◽  
Food Supply Chain ◽  
Multi Objective ◽  
Proposed Model

Traditional logistics management has not focused on environmental concerns when designing and optimizing food supply chain networks. However, the protection of the environment is one of the main factors that should be considered based on environmental protection regulations of countries. In this thesis, environmental concerns with a mathematical model are investigated to design and configure a multi-period, multi-product, multi-echelon green meat supply chain network. A multi-objective mixed-integer linear programming formulation is developed to optimize three objectives simultaneously: minimization of the total cost, minimization of the total CO2 emissions released from transportation, and maximization of the total capacity utilization. To demonstrate the efficiency of the proposed optimization model, a green meat supply chain network for Southern Ontario, Canada is designed. A solution approach based on augmented εε-constraint method is developed for solving the proposed model. As a result, a set of Pareto-optimal solutions is obtained. Finally, the impacts of uncertainty on the proposed model are investigated using several decision trees. Optimization of a food supply chain, particularly a meat supply chain, based on multiple objectives under uncertainty using decision trees is a new approach in the literature. Keywords: Meat supply chain; Decision tree; Multi-objective programming; Mixed-integer linear programming; Augmented εε-constraint.

Strategic Issues of Supply Chain Design and Management

2011 ◽  
pp. 19-34
Author(s):  
Nooshin Heidari ◽  
Shabnam Rezapour
Keyword(s):  
Supply Chain ◽  
Physical Structure ◽  
Supply Chain Design ◽  
Strategic Issues ◽  
Solution Methods

A supply chain (SC) is composed of different facilities and also their definite roles with the aim of delivering goods or services to the customer in an effective way. Obviously the physical structure of each SC has an important role in its performance. In this chapter, the authors aim to describe SC network (SCN) design definition, classification and related issues to this subject, models and solution methods. At the end, the conclusion is provided.

scholarly journals Determining nodal capacities for military distribution problems

2019 ◽  
Vol 3 (2) ◽  
pp. 110-130 ◽  
Author(s):  
Dave C. Longhorn ◽  
Joshua R. Muckensturm
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
The United States ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Multiple Time ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Content Type ◽  
Distribution Problems

Purpose This paper aims to introduce a new mixed integer programming formulation and associated heuristic algorithm to solve the Military Nodal Capacity Problem, which is a type of supply chain network design problem that involves determining the amount of capacity expansion required at theater nodes to ensure the on-time delivery of military cargo. Design/methodology/approach Supply chain network design, mixed integer programs, heuristics and regression are used in this paper. Findings This work helps analysts at the United States Transportation Command identify what levels of throughput capacities, such as daily processing rates of trucks and railcars, are needed at theater distribution nodes to meet warfighter cargo delivery requirements. Research limitations/implications This research assumes all problem data are deterministic, and so it does not capture the variations in cargo requirements, transit times or asset payloads. Practical implications This work gives military analysts and decision makers prescriptive details about nodal capacities needed to meet demands. Prior to this work, insights for this type of problem were generated using multiple time-consuming simulations often involving trial-and-error to explore the trade space. Originality/value This work merges research of supply chain network design with military theater distribution problems to prescribe the optimal, or near-optimal, throughput capacities at theater nodes. The capacity levels must meet delivery requirements while adhering to constraints on the proportion of cargo transported by mode and the expected payloads for assets.

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.

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