R. Ghasemy Yaghin and P. Sarlak
This paper studies the textile supply chain tactical planning under demand fuzziness through considering environmentally friendly and social responsibility. Hence, carbon emission…
Abstract
Purpose
This paper studies the textile supply chain tactical planning under demand fuzziness through considering environmentally friendly and social responsibility. Hence, carbon emission in textile production and transportation is considered along with supply chain profitability.
Design/methodology/approach
The authors present a fuzzy multi-objective mathematical optimization model with credibilistic chance constraints to determine the fabric procurement quantities and production plan under uncertainty. The solution procedure makes use of credibility measure and fuzzy aggregation operator to attain compromise solutions.
Findings
A trade-off among carbon emissions, social performance and supply chain total profit is conducted. The analyses indicate the importance of transportation costs and carbon emission while determining the supply chain's tactical plan.
Originality/value
The textile supply chain's social sustainability alongside carbon emissions of textile operations is contemplated to provide apparel production and distribution logistics planning under uncertainty. In doing so, the authors propose a hybrid credibility-possibility mathematical optimization model to determine a compromise solution for textile managers.
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R. Ghasemy Yaghin and P. Sarlak
This paper aims to propose an integrated supplier selection, order allocation, transportation planning model, along with investment planning for corporate social responsibility…
Abstract
Purpose
This paper aims to propose an integrated supplier selection, order allocation, transportation planning model, along with investment planning for corporate social responsibility (CSR), over a given multi-period horizon under uncertainty. Furthermore, a customer’s behavior to pay more money for items with CSR attributes is considered in the total market demand.
Design/methodology/approach
The objective functions, i.e. social value of purchasing, total profit (TP), total delivery lead-time, total air pollution, total water pollution and total energy consumption with regard to a number of constraints are jointly considered in a multi-product system. It is worth noting that operational- and sustainable-related parameters are usually vague and imprecise in this area. Therefore, this paper develops a new fuzzy multi-objective optimization model to capture this inherent fuzziness in critical data.
Findings
Through the numerical examples in the textile industry, the application of the model and usefulness of solution procedures are carried out. The numerical results obtained from the proposed approach indicate the efficiency of the solution algorithm in different instances. Moreover, the authors observe that social investment of the buyer, to stimulate market demand, can affect the TP and also involve the total contribution of suppliers in social responsibility.
Originality/value
This research work concentrates on providing a procurement and inventory model through the lens of sustainability to enable textile supply chain managers and related industries to apply the approach to their inventory control and supply management. Totally, the proposed methodology could be applied by many fabric buyers of textile industry tackling purchasing issues and attempting to perfect understanding of social supply chains.
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Pham Duc Tai, Krit Jinawat and Jirachai Buddhakulsomsiri
Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a…
Abstract
Purpose
Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a trade-off between financial and environmental aspects of these decisions, this paper aims to determine an optimal location, among candidate locations, of a new logistics center, its capacity, as well as optimal network flows for an existing distribution network, while concurrently minimizing the total logistics cost and gas emission. In addition, uncertainty in transportation and warehousing costs are considered.
Design/methodology/approach
The problem is formulated as a fuzzy multiobjective mathematical model. The effectiveness of this model is demonstrated using an industrial case study. The problem instance is a four-echelon distribution network with 22 products and a planning horizon of 20 periods. The model is solved by using the min–max and augmented ε-constraint methods with CPLEX as the solver. In addition to illustrating model’s applicability, the effect of choosing a new warehouse in the model is investigated through a scenario analysis.
Findings
For the applicability of the model, the results indicate that the augmented ε-constraint approach provides a set of Pareto solutions, which represents the ideal trade-off between the total logistics cost and gas emission. Through a case study problem instance, the augmented ε-constraint approach is recommended for similar network design problems. From a scenario analysis, when the operational cost of the new warehouse is within a specific fraction of the warehousing cost of third-party warehouses, the solution with the new warehouse outperforms that without the new warehouse with respective to financial and environmental objectives.
Originality/value
The proposed model is an effective decision support tool for management, who would like to assess the impact of network planning decisions on the performance of their supply chains with respect to both financial and environmental aspects under uncertainty.
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Seyed Mojtaba Taghavi, Vahidreza Ghezavati, Hadi Mohammadi Bidhandi and Seyed Mohammad Javad Mirzapour Al-e-Hashem
This paper aims to minimize the mean-risk cost of sustainable and resilient supplier selection, order allocation and production scheduling (SS,OA&PS) problem under uncertainty of…
Abstract
Purpose
This paper aims to minimize the mean-risk cost of sustainable and resilient supplier selection, order allocation and production scheduling (SS,OA&PS) problem under uncertainty of disruptions. The authors use conditional value at risk (CVaR) as a risk measure in optimizing the combined objective function of the total expected value and CVaR cost. A sustainable supply chain can create significant competitive advantages for companies through social justice, human rights and environmental progress. To control disruptions, the authors applied (proactive and reactive) resilient strategies. In this study, the authors combine resilience and social responsibility issues that lead to synergy in supply chain activities.
Design/methodology/approach
The present paper proposes a risk-averse two-stage mixed-integer stochastic programming model for sustainable and resilient SS,OA&PS problem under supply disruptions. In this decision-making process, determining the primary supplier portfolio according to the minimum sustainable-resilient score establishes the first-stage decisions. The recourse or second-stage decisions are: determining the amount of order allocation and scheduling of parts by each supplier, determining the reactive risk management strategies, determining the amount of order allocation and scheduling by each of reaction strategies and determining the number of products and scheduling of products on the planning time horizon. Uncertain parameters of this study are the start time of disruption, remaining capacity rate of suppliers and lead times associated with each reactive strategy.
Findings
In this paper, several numerical examples along with different sensitivity analyses (on risk parameters, minimum sustainable-resilience score of suppliers and shortage costs) were presented to evaluate the applicability of the proposed model. The results showed that the two-stage risk-averse stochastic mixed-integer programming model for designing the SS,OA&PS problem by considering economic and social aspects and resilience strategies is an effective and flexible tool and leads to optimal decisions with the least cost. In addition, the managerial insights obtained from this study are extracted and stated in Section 4.6.
Originality/value
This work proposes a risk-averse stochastic programming approach for a new multi-product sustainable and resilient SS,OA&PS problem. The planning horizon includes three periods before the disruption, during the disruption period and the recovery period. Other contributions of this work are: selecting the main supply portfolio based on the minimum score of sustainable-resilient criteria of suppliers, allocating and scheduling suppliers orders before and after disruptions, considering the balance constraint in receiving parts and using proactive and reactive risk management strategies simultaneously. Also, the scheduling of reactive strategies in different investment modes is applied to this problem.
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He Huang, Weining Wang and Yujie Yin
This study aims to focus on the clothing recycling supply chain and aims to provide optimal decisions and managerial insights into supply chain strategies, thereby facilitating…
Abstract
Purpose
This study aims to focus on the clothing recycling supply chain and aims to provide optimal decisions and managerial insights into supply chain strategies, thereby facilitating the sustainable development of the clothing industry.
Design/methodology/approach
Based on previous single- and dual-channel studies, game theory was employed to analyze multiple recycling channels. Concurrently, clothing consumer types were integrated into the analytical models to observe their impact on supply chain strategies. Three market scenarios were modeled for comparative analysis, and numerical experiments were conducted.
Findings
The intervention of fashion retailers in the clothing recycling market has intensified competition across the entire market. The proportions of various consumer types, their preferences for online platforms and their preference for the retailer’s channel influence the optimal decisions and profits of supply chain members. The diversity of recycling channels may enhance the recycling volume of clothes; however, it should meet certain conditions.
Originality/value
This study extends the existing theory from a channel dimension by exploring multiple channels. Furthermore, by investigating the classifications of clothing consumers and their influence on supply chain strategies, the theory is enhanced from the consumer perspective.
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Fereshte Shabani-Naeeni and R. Ghasemy Yaghin
In the data-driven era, the quality of the data exchanged between suppliers and buyer can enhance the buyer’s ability to appropriately cope with the risks and uncertainties…
Abstract
Purpose
In the data-driven era, the quality of the data exchanged between suppliers and buyer can enhance the buyer’s ability to appropriately cope with the risks and uncertainties associated with raw material purchasing. This paper aims to address the issue of supplier selection and purchasing planning considering the quality of data by benefiting from suppliers’ synergistic effects.
Design/methodology/approach
An approach is proposed to measure data visibility’s total value using a multi-stage algorithm. A multi-objective mathematical optimization model is then developed to determine the optimal integrated purchasing plan in a multi-product setting under risk. The model contemplates three essential objective functions, i.e. maximizing total data quality and quantity level, minimizing purchasing risks and minimizing total costs.
Findings
With emerging competitive areas, in the presence of industry 4.0, internet of things and big data, high data quality can improve the process of supply chain decision-making. This paper supports the managers for the procurement planning of modern organizations under risk and thus provides an in-depth understanding for the enterprises having the readiness for industry 4.0 transformation.
Originality/value
Various data quality attributes are comprehensively subjected to deeper analysis. An applicable procedure is proposed to determine the total value of data quality and quantity required for supplier selection. Besides, a novel multi-objective optimization model is developed to determine the purchasing plan under risk.
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José Leão, Leydiana de Sousa Pereira and Maria Luiza Xavier De Holanda Cavalcanti
Textile manufacturers worldwide are reformulating their networks, often outsourcing them to maintain a competitive advantage and increase market share. From this perspective, the…
Abstract
Purpose
Textile manufacturers worldwide are reformulating their networks, often outsourcing them to maintain a competitive advantage and increase market share. From this perspective, the purpose of this study is support the partnership selection process to develop a sustainable chain that effectively meets customer needs. Brazil has the largest textile and apparel chain in the West and is distinguished by its completeness, from fiber production, spinning, weaving, knitting, finishing and sewing to fashion shows. However, a firm’s relationship, especially in the production stage, is based on informal contracts, which result in a negative operational impact.
Design/methodology/approach
A methodological framework was developed based on a stable matching process to determine the optimal supplier network structure. This study presents a model application for the denim apparel chain in northeast Brazil.
Findings
In these environments, providing choices and recommending suppliers can be beneficial for effectively attending to demand requests, reducing production costs and improving quality through collaboration with sense relationships in a network. Thus, this study presents a better match from the negotiators’ perspective.
Originality/value
The findings of this research are of primary interest for guiding collaborative network composition in the textile and apparel chain. In particular, apparel domain companies can improve their effectiveness in decision-making by measuring the characteristics and potential of all companies involved in networks.
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Mahmoud Salari, Emad Hasani Malekshah, Mohammad Reza Sarlak, Masoud Hasani Malekshah and Mohammad Pilfoush
The purpose of this paper is to investigate the three-dimensional natural convection and entropy generation in a cuboid enclosure filled with two immiscible fluids of nanofluid…
Abstract
Purpose
The purpose of this paper is to investigate the three-dimensional natural convection and entropy generation in a cuboid enclosure filled with two immiscible fluids of nanofluid and air.
Design/methodology/approach
One surface of the enclosure is jagged and another one is smooth. The finite volume approach is applied for computation. There are two partially side heaters. Furthermore, the Navier–Stokes equations and entropy generation formulation are solved in the 3D form.
Findings
The effects of different governing parameters, such as the jagged surface (JR=0, 0.02, 0.04, 0.08, 0.12 and 0.16), Rayleigh number (103⩽Ra⩽106) and solid volume fraction of nanofluid (φ=1, 1.5, 2 vol%), on the fluid flow, temperature field, Nusselt number, volumetric entropy generation and Bejan number are presented, comprehensively. The results indicate that the average Nusselt number increases with the increase in the Rayleigh number and solid volume fraction of nanofluid. Moreover, the flow structure is significantly affected by the jagged surface.
Originality/value
The originality of this work is to analyze the natural-convection fluid flow and heat transfer under the influence of jagged surfaces of electrodes in high-current lead–acid batteries.
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Masoud Azarbik and Mostafa Sarlak
This paper aims to report how one can assess the transient stability of a power system by using stacked auto-encoders.
Abstract
Purpose
This paper aims to report how one can assess the transient stability of a power system by using stacked auto-encoders.
Design/methodology/approach
The proposed algorithm works in a power system equipped with the wide area measurement system. To be more exact, it needs pre- and post-disturbance values of frequency sent from phasor measurement units.
Findings
The authors have investigated the performance of the proposed method. Going through details, the authors have simulated many contingencies, and then have predicted the transient stability in each of which by using the proposed algorithm.
Originality/value
The results demonstrate that the algorithm is fast, and it has acceptable performance under different circumstances including the change of system topology and failures of telecommunication channels.