Supply chain management
Fatemeh Kangi; Seyed Hamid Reza Pasandideh; Esmaeil Mehdizadeh; Hamed Soleimani
Abstract
In recent years, the expansion of social responsibility concept, increased environmental considerations, economic incentives and governmental pressure on manufacturers for waste management have caused organizations to focus attention on the development of closed-loop supply chains (CLSC) and reverse ...
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In recent years, the expansion of social responsibility concept, increased environmental considerations, economic incentives and governmental pressure on manufacturers for waste management have caused organizations to focus attention on the development of closed-loop supply chains (CLSC) and reverse logistics (RL) processes. The adoption of these approaches, will enable organizations to simultaneously meet economic, social and environmental goals and consider the manufacturing cycle from supply and production to reuse of products. Hence, this study deals with an optimization model within the framework of a multi-echelon, multi-product and multi-period CLSC with hybrid facilities where cross-docking strategy and vehicle routing with soft time windows have been included in the model. In the problem defined as a MILP model, decisions are made simultaneously at three levels of strategic, tactical and operational. Furthermore, to tackle the NP-hard problem and achieve near-to-optimal results in reasonable time, two meta-heuristic algorithms, NRGA and MOPSO are developed and the algorithms’ parameters are tuned using the Taguchi method. Finally, the computational results are examined by the performance measures and statistical analysis and the sensitivity analysis is performed regarding the impacts of demand and rate of returned product on the objective functions’ values.
Supply chain management
Pooria Malekinejad; Seyed Haidar mirfakhradini; Ali Morovati sharifabadi; Seyed Mahmood Zanjirchi
Abstract
The increasing use of electronic goods worldwide has led to a significant increase in the amount of waste generated from their consumption, resulting in a major environmental concern. In response, this study aims to provide a systemic framework for reducing electronic waste by considering the benefits ...
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The increasing use of electronic goods worldwide has led to a significant increase in the amount of waste generated from their consumption, resulting in a major environmental concern. In response, this study aims to provide a systemic framework for reducing electronic waste by considering the benefits of a closed-loop sustainable supply chain. To achieve this goal, a systematic literature review was conducted to identify influential factors related to the green supply chain. Based on the identified factors in this section regarding electronic waste, a systematic framework was devised for the technology park companies' chain in Yazd. Accordingly, utilizing fuzzy cognitive mapping technique based on the current state, a systemic structure was formed. The statistical population of this study consisted of industry experts in e-waste in Iran. The initial criterion for identifying these individuals was having at least one international research publication or a minimum of 10 years of work experience in this field. These individuals were selected using the snowball sampling method. After completing the snowball sampling process, 72 experts were selected. Based on this framework, forward and backward scenarios were created to offer practical solutions for addressing the problem of electronic waste in Iran. The results of this study suggest that instead of discarding a significant portion of electronic waste, efforts should be focused on cost reduction through better recycling processes. By implementing a closed-loop sustainable supply chain, businesses can recover valuable resources from electronic waste, reduce their carbon footprint, and ultimately contribute to creating a more sustainable future.
production planning
Ommolbanin Yousefi; Saeed Rezaeei Moghadam; Neda Hajheidari
Abstract
One of the most important decisions taken in a supply chain is the issue of aggregate production planning where a program-within a medium time-range-- is determined for optimum manufacturing of all products using shared equipment and resources. This research presents a multi-objective model that helps ...
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One of the most important decisions taken in a supply chain is the issue of aggregate production planning where a program-within a medium time-range-- is determined for optimum manufacturing of all products using shared equipment and resources. This research presents a multi-objective model that helps the decision makers to make such decisions. The proposed model comprises four main objectives, the first one of which considers minimizing costs (including costs of manufacturing product, supplying, maintenance, inventory stock shortage, and expenditures related to man power). The second objective is defined as maximizing customers’ satisfaction. Minimizing suppliers’ satisfaction makes up the third objective and maximizing the quality of the manufactured products constitutes the fourth objective. In this model, the demand parameter is investigated under uncertain conditions; hence, other parameters influenced by this parameter are also presented under uncertain conditions occurring within three differing scenarios. This model is solved through LP- metric and the LINGO v14.0.1.55 software. At first the model is solved by means of numerical example; then it is solved by the actual data that are related to a military industry. Finally, process, variables like inventory level, overtime work hours etc, are valued with the help of closed-loop supply chain of the proposed model.
Supply chain management
Arash Khosravi Rastabi; Seyed Reza Hejazi Taghanaki; Shahab Sadri; Anil Kumar; Hossein Arshad
Abstract
The objective of this study is to model a dynamic redesigning closed-loop supply chain network with capacity planning in order to minimize the costs of the network. The structure of this model consists of existing facilities including manufacturing plants, distribution and reworking centers. Any such ...
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The objective of this study is to model a dynamic redesigning closed-loop supply chain network with capacity planning in order to minimize the costs of the network. The structure of this model consists of existing facilities including manufacturing plants, distribution and reworking centers. Any such structure should change due to fluctuations in demand in order to meet customer demand. Establishing new facilities, closing the existing ones, and adding discrete capacity levels to facilities, are among the decisions which lead to necessary changes in network structure. To make the issue more realistic, it is assumed that demand and returned products are stochastic. To solve the problem, a two-stage stochastic mixed integer linear programming is modelled, followed by writing a robust counterpart of the MILP model program. An accelerated Benders decomposition algorithm is proposed to solve this model. To increase the convergence trend of this proposed algorithm, valid-inequalities and Pareto optimal cut are combined to the model. The expected performance improvement based on applying valid-inequalities and Pareto optimal cut is expressed through numerical results obtained from different samples.