فهرس المقالات Mixed-integer programming

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  1 - A Facility Location Problem in a Green Closed-Loop Supply Chain Network Design by Considering Defective Products
  Zahra Zanjani Foumani Ensieh Ghaedy heidary Amir Aghsami Masoud Rabbani
  10.30495/jiei.2022.1942069.1168
  This paper proposes a bi-objective model for a green closed-loop supply chain network design. Four levels for forward and five levels for reverse flow were considered, including plants, distribution centers, online retailers, traditional retailers and customers for forw أکثر

  This paper proposes a bi-objective model for a green closed-loop supply chain network design. Four levels for forward and five levels for reverse flow were considered, including plants, distribution centers, online retailers, traditional retailers and customers for forward flow and customers, collecting centers, disposal centers, repair centers and plants for the reverse flow. The objectives are minimizing the GHG emission and maximizing profit by considering defective products and a second market for these products. Also, online retailers were considered alongside with traditional ones, since the Covid-19 pandemic has led to increase in the amount of online shopping. GAMS software and the Lpmetric technique were used to solve the model in the small and medium sizes. However, for the large size, we used Grasshopper Optimization Algorithm (GOA) as a meta-heuristic approach since solving the large size problem with GAMS is a complicated and time-consuming process. We provided Numerical and computational results to prove the efficiency and feasibility of the presented model. Finally, the managerial insights and future works were provided. تفاصيل المقالة
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  2 - The sustainable supply chain of CO2 emissions during the coronavirus disease (COVID-19) pandemic
  sina abbasi Maryam Daneshmand-Mehr Armin Ghane Kanafi
  10.30495/jiei.2022.1942784.1169
  This investigation aims to demonstrate an application mathematical model of the sustainable closed-loop supply chain network (SCLSCN) during the COVID-19 pandemic. The suggested model can illustrate the trade-offs between environmental, economic, and social dimensions d أکثر

  This investigation aims to demonstrate an application mathematical model of the sustainable closed-loop supply chain network (SCLSCN) during the COVID-19 pandemic. The suggested model can illustrate the trade-offs between environmental, economic, and social dimensions during the epidemic. The costs include the normal costs and the hygienic costs. The total cost was increased in the COVID-19 pandemic by 25.14 %. The novelty social aspects of this model include the average number of lost days caused by COVID-19 damage and the number of created new job opportunities related to COVID-19. The average number of lost days caused by damages increased by 51.64 % during COVID-19. The CO2 emissions were decreased by17.42 %. This paper presents a multi-objective mixed-integer programming (MOMIP) problem. We use the weighted sum method (WSM) approach for the scalarization approach. To optimize the process, Lingo software has been used. Our contributions to this research are i) Suggested an application model of SSC to show better the trade-offs between three aspects of sustainability in the COVID-19 pandemic and lockdown periods, ii) Designing the hygienic and safe SC for employees, iii) developing the social and economic indicators, iv) We have found the negative and positive impacts of COVID-19 and lockdowns on SC, v) Finally, we analyze the mathematical model and discuss managerial implications. Therefore, this investigation tries to fill this gap for COVID-19 condition disaster. This research's novelty is to simultaneously present a MOMIP model, COVID-19 issues, and hygienic rules, in a closed-loop supply chain (CLSC) framework. تفاصيل المقالة
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  3 - Approximate Solution of General mp-MILP Problems and Its Application in Urban Traffic Networks
  Maryam Mahmoudi Aghileh Heydari Ali Karimpour
  10.30495/ijm2c.2023.1951076.1244
  The multi-parametric programming (mp-P) is designed to minimize the number of unnecessary calculations to obtain the optimal solution under uncertainty, and since we widely encounter that kind of problem in mathematical models, its importance is increased. Although mp-P أکثر

  The multi-parametric programming (mp-P) is designed to minimize the number of unnecessary calculations to obtain the optimal solution under uncertainty, and since we widely encounter that kind of problem in mathematical models, its importance is increased. Although mp-P under uncertainty in objective function coefficients (OFC) and right-hand sides of constraints (RHS) has been highly considered and numerous methods have been proposed to solve them so far, uncertainty in the coefficient matrix (i.e., left-hand side (LHS) uncertainty) has been less considered. In this work, a new method for solving multi-parametric mixed integer linear programming (mp-MILP) problems under simultaneous uncertainty OFC, RHS, and LHS is presented. The method consists of two stages which in the first step, using tightening McCormick relaxation, the boundaries of the bilinear terms in the original mp-MILP problem are improved, the approximate model of the problem is obtained based on the improved boundaries of the first stage, and finally, an algorithm is presented to solve these kinds of problems. The efficiency of the proposed algorithm is investigated via different examples and the number of required calculations for solving the problem in different partitioning factors is compared. Also, model predictive control (MPC) using mp-P is designed for an example of an urban traffic network to examine the practical application of the proposed algorithm. تفاصيل المقالة