supply chain management analyzing/modelling
Javad Mohammadghasemi; Seyyed Esmaeil Najafi; Mohammad Fallah; Mohammad Reza Nabatchian
Abstract
Purpose: This paper focuses on modeling a sustainable electricity industry supply chain network under uncertainty. The aim of presenting this supply chain network is to meet customer demands for solar panels to generate clean energy.Methodology: A mixed-integer linear programming model, including facility ...
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Purpose: This paper focuses on modeling a sustainable electricity industry supply chain network under uncertainty. The aim of presenting this supply chain network is to meet customer demands for solar panels to generate clean energy.Methodology: A mixed-integer linear programming model, including facility location, supplier selection, optimal flow allocation, and determination of the optimal price of solar panels in the network, is considered. The sustainability objectives of the model include maximizing the profit of the supply chain network, minimizing greenhouse gas emissions, and maximizing reliability. A robust optimization method is also considered to control uncertain parameters, and precise and innovative techniques are used to solve the model.Findings: The results of the model show that with an increase in network reliability, the current net value in the network decreases, and greenhouse gas emissions in the network increase. Additionally, the analysis of the results shows that with an increase in the network's uncertainty rate, the network's current net value and reliability decrease, and greenhouse gas emissions increase. Finally, the statistical test results also show that there was no significant difference between the averages of the number of practical solutions, the maximum spread, and the metric distance between the two algorithms, and only a significant difference exists between the solution times of the two algorithms. The results of the presented solution methods demonstrate their high efficiency in solving the sustainable electricity industry supply chain model.Originality/Value: In the proposed model, essential decisions such as supplier selection, establishment of production centers, optimal product flow allocation, and pricing of solar panels are made. On the other hand, further analyses of 15 numerical examples show the high efficiency of the MOALO and MOWOA algorithms compared to the epsilon-constraint method.
Robust optimization
Mohamad Ali Movafaghpour
Abstract
Purpose: In many real-world optimization problems, we are facing uncertainties in parameters describing the problem. In general, as a simplifying assumption, uncertainty is ignored. In the school bus routing problem, there are uncertain parameters that are assumed to have deterministic values. As a result ...
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Purpose: In many real-world optimization problems, we are facing uncertainties in parameters describing the problem. In general, as a simplifying assumption, uncertainty is ignored. In the school bus routing problem, there are uncertain parameters that are assumed to have deterministic values. As a result of this simplifying assumption, the obtained solutions may be mismatched with the real world. This issue arose by violating some hard constraints.Methodology: In this research, a mixed linear integer programming for school bus routing with mixed loading by using a heterogeneous fleet is presented. The uncertainty of travel times is modeled as interval numbers. We propose a heuristic algorithm to generate extreme scenarios. Each scenario is generated in order to make the last found optimal solution into an infeasible one as much as possible.Findings: Experimental results show that deploying this novel algorithm for generating extreme scenarios, efficiently produces diverse scenarios. After the scenario generation algorithm is converged, the intersection of the feasible optimal solutions under diverse scenarios is extracted as robust sub-tours or robust trips.Originality/Value: It is the first time to apply the notions of robust optimization using the extreme scenarios generation scheme. At each iteration of the extreme scenario’s generation, the most conflicting scenario against a given optimum solution is generated. The main advantage of this method over other present robust optimization methods is its emphasis on maintaining the feasibility of the optimal solution when dealing with the most diverse set of uncertainty scenarios while keeping the computational effort needed as low as desired.
supply chain management analyzing/modelling
Hamid Saffari; Morteza Abbasi; Jafar Gheidar-Kheljani
Abstract
Purpose: This research proposes a multi-objective and robust model considering both cost and risks related to the environment (water consumption and environmental pollution), social responsibility (working conditions and employee health), operations (change in demand and return rates), and disruption ...
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Purpose: This research proposes a multi-objective and robust model considering both cost and risks related to the environment (water consumption and environmental pollution), social responsibility (working conditions and employee health), operations (change in demand and return rates), and disruption (accs and diseases such as COVID-19) in the supply chain, using horizontal collaboration to deal with it.Methodology: In this research, mixed-integer linear programming and robust optimization technique have been used for closed-loop supply chain network design and a multi-objective method has been developed to solve the problem and create Pareto spaces.Findings: The results of the calculations show the effect of failure probability on the capacity of the facility, the total cost of the network and the degree of collaboration between members of the supply chain to deal with the risk. Also, the amount of cost required for allocation to reliable and unreliable facilities and also creating a suitable Pareto space for deciding on the optimal choice of facilities, capacity and flow between them and iron and steel production technology, according to sustainability and social responsibility indicators, are other research findings.Originality/Value: In this study, for the first time, the design of a robust, sustainable, and resilient network of iron and steel under different risks has been studied. Horizontal collaboration has been used as a new approach to deal with risk and solution method for multi-objective problems has been developed. Using the results of this study, the decision-maker can make informed decisions about the supply chain under risk conditions by considering suitability for each of the objectives.
Robust optimization
Shima Roosta; Seyed Milad Mirnajafi Zadeh; Hamid Bazargan Harandi
Abstract
Purpose: Location-Routing Problem (LRP) is a strategic supply chain design problem aimed at meeting customer demands. LRPs involve selecting one or more depot sites from a set of potential locations and determining the best routes to connect them to demand points. With the rising awareness about the ...
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Purpose: Location-Routing Problem (LRP) is a strategic supply chain design problem aimed at meeting customer demands. LRPs involve selecting one or more depot sites from a set of potential locations and determining the best routes to connect them to demand points. With the rising awareness about the environmental impacts of transportation over the past years, using green logistics to mitigate these impacts has become increasingly important.Methodology: To compensative a gap in the literature, this paper presents a robust bi-objective Mixed-Integer Linear Programming (MILP) model for the Green Capacitated Location-Routing Problem (G-CLRP) with demand uncertainty and the possibility of failure in depots and routes.Findings: The final result of this robust multi-objective model is to set up the depots and select the routes that offer the highest reliability (maximizing network service) while imposing the lowest cost and environmental pollution. The paper also provides a numerical analysis and a sensitivity analysis of the solutions of the model.Originality/Value: Determining backup depots and increasing network serviceability for LRPs.
Data Envelopment Analyses
Mostafa Radsar; Aliyeh Kazemi; Mohammadreza Mehregan
Abstract
Purpose: It is important to consider the uncertainty in the data, and know how to deal with it when evaluating efficiency by using data envelopment analysis; since the presence of small deviations in the data can lead to significant changes in efficiency results. However, in the real world in many cases, ...
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Purpose: It is important to consider the uncertainty in the data, and know how to deal with it when evaluating efficiency by using data envelopment analysis; since the presence of small deviations in the data can lead to significant changes in efficiency results. However, in the real world in many cases, the data is uncertain. The purpose of this paper is to present a robust model of network data envelopment analysis in order to measure efficiency in the presence of uncertainty.Methodology: A new approach to evaluate efficiency for network data envelopment analysis is first proposed. The definitive method presented in this paper involves undesirable output and can be used for different structures in network data envelopment analysis. Next by extending, the proposed model for uncertain data a new robust network data envelopment analysis model is presented for three-stage networks with undesirable outputs.Findings: The proposed model is used to evaluate the electricity regions of Iran. These regions involve a three-step process with undesirable outputs in some stages. The results show that the proposed model achieves the efficiency of the steps and the total efficiency simultaneously. In addition, the overall network efficiency score can be a basis to rank the areas.Originality/Value: The proposed model is a new model in the field of efficiency evaluation in conditions of uncertainty and having an undesirable output.
supply chain management analyzing/modelling
elham kouchaki tajani; Armin Ghane Kanafi; Maryam Daneshmand-Mehr; Ali-Asghar HoseinZadeh
Abstract
Purpose: Designing a logistic network is a vital and strategic issue that provides the optimal platform for effective and useful management of supply chain. For this purpose, in this paper, a multi-echelon, multi-product, multi-period and multi-objective sustainable dual-channel closed-loop supply chain ...
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Purpose: Designing a logistic network is a vital and strategic issue that provides the optimal platform for effective and useful management of supply chain. For this purpose, in this paper, a multi-echelon, multi-product, multi-period and multi-objective sustainable dual-channel closed-loop supply chain network has been designed taking into account the technology of RFID. Simultaneously this model seeks to maximize the profits and social responsibility of the supply chain network while it minimizes the whole delay in delivery time and environmental pollution. Also, because definitive models are incapable of understanding the complexities of real-world applications, so this paper also addresses systemic and environmental uncertainties.Methodology: In this study, the scenario-based stochastic robust programming optimization technique is used to deal with the uncertainty of the parameters and to deal with the uncertainty of the parameters, and due to the multi-objective model and for validation and model exact solution in small dimensions of a new robust augmented ε‑constraint method (AUGMECON‑R) is used to achieve the best balance between the objectives. Also, since the problem is of np-hard class, two NSGA-II and MOPSO algorithms were used to solve the model in larger dimensions.Findings: The results show that this model has acceptable efficiency that due to the uncertainty of some parameters.Originality/Value: The proposed model includes mathematical formulas in a certain and robust state that allows the establishment of several complicated characteristics in the above text along with direct and indirect selling channels and repairing centers and secondary costumers create the new design of supply chain that can be supreme model for the managers and professionals with the wide application especially from strategic view.
supply chain management analyzing/modelling
Javid Ghahremani Nahr; Mehrnaz Bathaee
Abstract
Purpose: In this paper, a humanitarian logistics network is designed considering the purchase contract in conditions of uncertainty. Due to the importance of such networks in the event of unforeseen events, the designed model seeks to determine the central and local warehouses as well as shelters to ...
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Purpose: In this paper, a humanitarian logistics network is designed considering the purchase contract in conditions of uncertainty. Due to the importance of such networks in the event of unforeseen events, the designed model seeks to determine the central and local warehouses as well as shelters to transport the injured. Also, determining the optimal amount of inventory and the correct way of transferring items and injured are other network decisions. In this article, the contract for purchasing items before and after the accident is concluded with suppliers in order to supply raw materials to the severity of the accident.Methodology: Due to the uncertainty in the model, the robust optimization method is used to control the uncertainty, and due to the NP-Hardness of the model, the new Gray Wolf-Genetics Algorithm (GGWA) is used to solve the model.Findings: The results show that contract operation has reduced the costs of the entire humanitarian logistics network. The comparison of the means of the objective function and the computational time shows the high speed of the GGWA algorithm in finding near-optimal solutions compared to the PSO and GA algorithms.Originality/Value: In this paper, a new model of humanitarian supply chain network has been designed, which has obtained very favorable results from the problem using the GGWA algorithm in the shortest time.
Optimization in science and engineering
Amir Parnianifard; Hamidreza Izadbakhsh
Abstract
Up to now, different tools have been introduced for analyses of process capability such as process capability indexes of Cp, Cpk and Cpm that developed for analyzing the capability of process and adapting the quality specifications of product. Most studies in the literature only consider the process ...
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Up to now, different tools have been introduced for analyses of process capability such as process capability indexes of Cp, Cpk and Cpm that developed for analyzing the capability of process and adapting the quality specifications of product. Most studies in the literature only consider the process with single capability variable, while there is a lack of studies that consider multi-variable processes. Cpm index has been defined with Taguchi overview over robust design. In this research, the metric Lp model has introduced to investigate the optimum decision variables by considering nominal is better quality specification and reparation Cpm index. We also expand the proposed model for such a processes with considering overall cost as well as process quality. At the end of research, numerical example has been presented to exhibit usage of proposed model for obtaining the best levels of process decision variables.
Robust optimization
Masomeh Hoseinpour; Alireza Fakharzadeh Jahromi
Abstract
In recent decades, the theory of robust optimization has been introduced as a powerful tool for optimizing uncertain processes. Regarding the Uncertainty of the glycemic load of consumed food, the main purpose of this article is to provide an optimal Iranian diet using a robust optimization to adjust ...
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In recent decades, the theory of robust optimization has been introduced as a powerful tool for optimizing uncertain processes. Regarding the Uncertainty of the glycemic load of consumed food, the main purpose of this article is to provide an optimal Iranian diet using a robust optimization to adjust the glycemic load in patients with type 2 diabetes. Diabetes type 2 is a devastating disease, in addition to cardiovascular disease, infectious and kidney diseases, causes insulin resistance and cancer and drugs of cholesterol-lowering have an increased risk of cardiovascular complications and incidence of cancer. Indeed, adjustment of nutrition is important to prevent and control or reduce the complications of diabetes. In this paper, due to the uncertainty of the glycemic load of foods, with collecting necessary nutritional information, the Iranian diet model is determined and analyzed by a robust optimization method. According to this, 75 cases of food (42 Iranian food, 10 Foodstuffs for breakfast, 20 types of fruits and fruit juices and 3 types of dairy products) have been studied locally. The benefits of this model are the ability to adapt according to the person's tastes and opinion of the nutritionist with minimizing changes for the current diet of the individual.