طراحی شبکه لجستیک حلقه بسته پایدار با در نظر گرفتن تقاضای چند حالته در شرایط عدم قطعیت

توجه به بازگرداندن محصولات به چرخه تولید نیاز استفاده از زنجیره تامین حلقه بسته را بالا برده و همچنین اثرات زیست محیطی ناشی از فعالیت‌های صنعتی و پیشرفت صنایع، احساس نیاز و علاقه‌مندی پژوهشگران را به طراحی زنجیره تامین پایدار با توجه به مسائل اقتصادی، زیست محیطی و مسائل اجتماعی بیش از پیش به خود جلب کرده است. بدین منظور، این مقاله یک مدل برنامه ریزی ریاضی فازی عدد صحیح چند هدفه برای طراحی یک زنجیره تامین حلقه بسته پایدار تحت شرایط عدم قطعیت ارائه می‌کند. مدل ارائه شده سعی می‌کند تا میزان سود و همچنین تاثیرات اجتماعی را بیشینه و میزان ورود گازهای آلاینده به محیط را کمینه کند. همچنین از آنجایی که علاوه بر عدم قطعیت، شک و تردید نیز تصمیم گیرنده را دچار چالش می کند، برای تعیین مقادیر پارامترها، از اعداد فازی ذوزنقه‌ای شهودی استفاده شده است. برای قطعی سازی توابع هدف و محدودیت‌های مدل به ترتیب از روش امید ریاضی و اندازه اعتبار شهودی توسعه داده شده است. سرانجام برای حل مساله چند هدفه قطعی بدست آمده، از روش برنامه ریزی فازی تعاملی استفاده شده است. به منظور کارایی و اعتبار سنجی مدل و روش حل پیشنهادی، سه مثال عددی در ابعاد مختلف طراحی و حل شده است.

designing a sustainable closed-loop logistics network considering the multi-mode demand in uncertain environment

the closed-loop supply chain is used in practice for several reasons. firstly, returning products to the production cycle is important for its operation. secondly, sustainability in the supply chain is a topic of interest for researchers, as the environmental impacts of industries are significant. in this paper, a multi-objective integer fuzzy mathematical programming model is presented to design a sustainable closed-loop supply chain under uncertain conditions. the proposed model aims to maximize profit and social impacts, while minimizing gas emissions into the environment. since decision makers face uncertainty and doubt, trapezoidal intuitionistic fuzzy numbers are employed to determine the parameter values in the model. to convert the objective functions and model constraints into crisp forms, the expected value and the intuitionistic credibility measure are developed for the objectives and constraints, respectively. finally, an interactive fuzzy programming approach is utilized to solve the crisp multi-objective problem. three numerical examples are designed and solved to validate the model and assess the efficiency of the proposed solution method.introductionsupply chain management encompasses techniques aimed at coordinating all aspects of the supply chain, from raw material procurement to product delivery or recovery, with the objective of minimizing total costs while addressing conflicts among chain partners. once raw materials have traversed the forward chain and been transformed into products or services, they may require repair, transformation, or proper disposal, which occurs within the reverse chain. the integration of forward and reverse supply chain methods gives rise to a closed-loop supply chain.today, one of the primary concerns for organizational managers in supply chain network design is the presence of uncertainties, such as disruptions and uncertain input parameters. uncertainties can have adverse effects on supply chain performance and decision-making at various network levels, including tactical, strategic, and operational decisions. as probabilistic planning necessitates historical data, which may not always be available or accurate, the theory of fuzzy sets can serve as a suitable option for expressing ambiguity and lack of certainty in parameters. in recent years, environmental factors have received increasing attention. there has been a growing recognition of the importance of environmental effects and the need to incorporate these effects alongside traditional indicators in supply chain design. environmental considerations are crucial not only for compliance with government regulations but also for improving the organization’s social standing from the customers’ perspective. moreover, with the rise of global warming and the accumulation of waste (both renewable and non-renewable, as well as electronic waste and ozone-depleting gases), the importance of managing and controlling these factors has become even more prominent. despite the significance of environmental issues, there remains a noticeable gap in the supply chain literature concerning the provision of mathematical models based on real-world conditions and efficient solution methods for this problem. this paper focuses on the design of a sustainable closed-loop logistics network that aims to maximize profitability and social factors while minimizing environmental factors. the proposed integrated network considers multi-product and multi-state customer demand under conditions of uncertainty. the significance of this research lies in simultaneously addressing economic, environmental, and social considerations in the modeling process, as previous studies have mostly focused on single or dual objectives.