supply chain management analyzing/modelling
Saeid Kalantari; Hamed Kazemipoor; Farzad Movahedi Sobhani; Seyyed Mohammad Hadji Molana
Abstract
Purpose: Establishing the structure and expansion of sustainable closed-loop supply chains is critical to meeting environmental, economic, and social standards to strengthen their position in competitive markets. This study aims to decide on operational and tactical levels to configure the Stable Closed ...
Read More
Purpose: Establishing the structure and expansion of sustainable closed-loop supply chains is critical to meeting environmental, economic, and social standards to strengthen their position in competitive markets. This study aims to decide on operational and tactical levels to configure the Stable Closed Chain Supply Chain Network (SCLSC) to maximize Net Present Value (NPV) and seek to minimize carbon emissions while maintaining environmentally friendly policies and considering inflation.Methodology: This paper considers a solid Fuzzy Robust Optimization (FRO) approach to deal with stable, closed-loop supply chain uncertainties. Also, due to the complexity of the model and its multi-objective, a new combined method of Heuristic algorithm (HA) and Multi-Choice Goal Programming with Utility Function (MCGP-UF) is used. The proposed Mixed Integer Linear Programming (MILP) model is applied in the electronics industry.Findings: The proposed model is evaluated in several experiments and discussed in different scenarios to confirm the efficiency and validity of the proposed model and method. The results were compared with the two factors of optimal gap and solution time, which showed the proper performance of the proposed method. Then, the tactical results and model strategy were presented for a case study in which the optimal flow between facilities, selection of suitable suppliers, selection of transportation type, and opening of facilities were presented. The findings showed that in different scenarios, the effective improvement of the obtained solutions by reducing the solution time by twenty percent could address large-scale problems.Originality/Value: By considering a new combined method of heuristic algorithm and multi-choice ideal programming with a utility function, this paper is done to solve the problem of designing a stable closed-loop supply chain network under uncertainty.
Combinatorial Optimization
MohammadSaviz Asadilari; Fariborz Jolai; Reza Tavakkoli-Moghaddam; Jafar Razmi
Abstract
By increasing the use of container transportation, one of the existing problems is the constant capacity of container terminals due to problems, such as lengthy construction process, lack of budget and space to build new locations, as well as lack of manpower. Also, this constant capacity leads to problems ...
Read More
By increasing the use of container transportation, one of the existing problems is the constant capacity of container terminals due to problems, such as lengthy construction process, lack of budget and space to build new locations, as well as lack of manpower. Also, this constant capacity leads to problems such as reduced trade relations, increased maintenance and warehousing costs, increased transportation costs, and increased loading and unloading times, as well as container allocation problems. To solve this problem without increasing the area of the terminal, this paper present a mathematical model to allocate containers that can be used not only to solve this problem, but also in other cases such as transportation and shipping used. Due to the size of problems used in this research, a heuristic algorithm, namely LOGIC algorithm is used. According to studies, carried out in the literature, this algorithm has not been used in relevant problems so far. Also, due to the development of the LOGIC algorithm in this paper, it can be used for other large-scale optimization problems. The development of the proposed algorithm can be improved to solve the layout problem of maritime containers with other real constraints.