نشریه پژوهشهای مهندسی صنایع در سیستمهای تولید
پیاپی 21 (پاییز و زمستان 1401)

Due to the special position of flow shop scheduling systems in production centers, these issues have received a lot of attention in recent years. One common assumption in these cases is the availability of machines on the planning horizon. In real industrial environments, a machine may be temporarily unavailable for reasons such as the need for preventative maintenance. Due to the importance of this issue, in the present study the flexible flow shop scheduling problem with reverse flows is investigated by considering the activity of preventive maintenance in which there are two flows of jobs (direct and reverse) that cover the same machines in opposite directions. An essential issue for modeling the flexible flow shop-scheduling problem is to consider the limitations of access to machines in order to perform preventive maintenance. The maintenance operation on each machine has a fixed duration and its beginning and end occur in a certain time window. For the mentioned problem, a Mixed Integer NonLinear Programing (MINLP) model is presented. The objective of this model is to minimize the maximal completion time of the jobs (i.e., the ma kespan). Due to the complexity of the model and the NP-hardness of the proposed problem, the Imperialist Competitive Algorithm (ICA) is proposed to solve large-scale problems. In order to evaluate the performance of the proposed algorithm, numerical sample problems in different sizes are solved using this algorithm, the General Algebraic Modeling System (GAMS) software as well as the genetic algorithm. Computational results demonstrate the effectiveness of the Imperialist Competitive Algorithm for the considered problem.

Receiving fast, flexible, reliable and low-cost delivery services by customers is one of the important challenges for the distribution of goods, especially in urban areas. After that, with the increase in demand and as a result, the increase in vehicles for the purpose of goods' transportation, it causes congestion in urban transportation networks. Therefore, in this study, the multi-fleet feeder vehicle routing problem is investigated in a situation where several trucks and motorcycles cooperate with each other to satisfy the demand at the same time. The feeding vehicle routing problem consists of a heterogeneous fleet of vehicles, including trucks and it makes it possible for motorcycles to pass in high-traffic areas and distribute urban traffic easily.  In fact, the feeder approach in the VRP is to reduce the number of times of returning to the main depot for loading and to save the cost and time of tours. Here, at first, a mathematical model is presented, then, due to the high complexity of the mixed integer programming model and in order to reduce the runtime of solving the model in large dimensions, the Lagrangian relaxation algorithm with the sub-gradient optimization approach is proposed. The results showed that with the increase in the dimensions of the problem, the runtime of the proposed algorithm is less compared to the outputs of GAMS. Also, the runtime saving resulting from solving the model with the Lagrangian relaxation algorithm is significant, and as a result, this algorithm is effective for solving the model.

In a green supply chain, preventing the disposal of used products and reusing them will help to protect the environment. The most important step in the closed-loop supply chain is the disassembly and recovery of used products and their reuse in producing new products. In this paper, we propose a new mixed-integer programming model to consider a multi-period multi-product disassembly scheduling problem based on parts commonality and partial disassembly. Considering partial disassembly is the main contribution of this paper. When the disassembly is partial, the parts with no demand will not disassemble; so, a lot of time and cost will be saved. The proposed model is solved using CPLEX Solver, and sensitivity analysis is deployed to validate the model and determine the proposed model's practical results. Numerical experiments shows that the CPLEX solver has a good efficiency for solving the developed model in small and medium dimensions.

Human factors engineering is a scientific area about collaboration between persons and other parameters of a system. It consists of theorems, principles and methods for designing based on the relief of operators and system performance. The main purpose of this paper is scheduling the orders and operators in a CMS regarding the human factors to minimize the orders’ tardiness and fatigue of operators. The fatigue, recovery, learning and forgetting are the human factors in this study, which affect the job rotation and shift scheduling. A mathematical model and a rolling horizon heuristic are developed as well as three groups of test problems each including five random problem instances. The rolling horizon algorithm was tested on the test problems and the results showed that non-overlapping mode with a length of 2 periods is the best choice. The heuristic algorithm solves large-scale instances with less than 3% optimality gaps in about 5.5 minutes while the MIP model needs about 2 hours. The results of linearization of the model showed that the conversion of the continuous variables into integer numbers is more efficient than the McCormick method. Sensitivity analysis shows that fatigue factor has a direct relation with tardiness and learning and also, the learning factor has a reverse relation with the both objectives of tardiness and mean fatigue.

Supply chain finance includes a set of innovative solutions to improve working capital in a supply chain. The purpose of this study is to provide a comprehensive framework for designing supply chain financial strategies by combining a finance-oriented perspective and a supply chain-oriented perspective, simultaneously. To achieve the research objective, the seven-step model proposed by Sandelowski and Barroso was used to analyze the content of the articles. The statistical population of this research includes international publications in the field of supply chain finance between 2000 and 2021. After collecting the related articles, the relevant codes were extracted and finally the reliability of the coding was confirmed by calculating the Cohen's kappa coefficient. According to the classification of codes extracted from selected articles, the components affecting the design and implementation of supply chain finance strategies were identified. This framework consists of 5 main categories including supply chain, financing instruments, actors, enablers and inhibitors and modeling. The reliability of this coding was also confirmed at the 95% confidence level by calculating the kappa index. The results of this study show that although several supply chain finance instruments are designed based on accounts receivable and accounts payable techniques, internal financing strategies through the use of surplus funds within the supply chain are not well developed. Also, based on the country's banking industry's need to increase income, in the modeling of external supply chain finance solutions, commercial banks can maximize their profits along with supply chain members at a rate higher than the risk-free interest rate.

Advertising is one of the most effective means of increasing sales of supply chain members. In order to increase sales and meet demand, chain members must coordinate their efforts. Since advertising and production decisions in the supply chain are interactive between members, it is necessary to create a form of integration or participation in decision-making. Two retailers and a manufacturer are part of the supply chain considered in this study. On the one hand, the manufacturer uses global advertisements to strengthen the business brand, and on the other hand, retailers use local advertisements to increase sales. The manufacturer participates in financing local advertising costs with retailers. Additionally, it is assumed that there are production capacity constraints for the manufacturer, as well as advertising budgets for each member of the supply chain. A manufacturer's limited capacity creates a competition between retailers to meet demand and an advertising budget restriction creates competition among them to attract the most participation in advertising expenses. The governing structure of the optimization model is a bi-level programming type where the manufacturer is at the first level and the competing retailers are at the second level. From the game theory perspective, a type of generalized Stackelberg-Nash game prevails between the players. A solution method based on variational inequalities is proposed to find the equilibrium of this game, and numerical analyses are provided to evaluate the model and solution method. Finally, managerial implications based on the results of numerical experiments have been proposed.

With the reduction of non-renewable energy sources and the increased energy costs in recent years, the decision-making model with energy and electricity consumption consideration is significant. Time-of-Use (ToU) policy is one of the incentive policies in the whole world that provides new opportunities to save electricity consumption and energy costs. This paper considers a batch processing machine scheduling problem with identical jobs and a two-objective function of minimizing the cost of electricity consumed by the machine and minimizing the makespan under the ToU policy. The processing time of jobs is considered fuzzy due to uncertainty in the real world. The effectiveness and efficiency of the proposed model and solution approach to reduce the electricity cost are demonstrated by carrying out two numerical experiments.

Through a cross-docking strategy in logistics, goods are unloaded from inbound trucks and loaded onto outbound trucks with minimal storage. The management of equipment and manpower involved in unloading goods, moving them within the terminal, and reloading them on outgoing trucks is one of the most challenging aspects of cross-docking management. In this paper, a new bi-objective mixed-integer linear programming model is presented for scheduling incoming and outgoing trucks in a cross-docking terminal with flexible doors, where the distance between doors and the time for moving trucks inside the cross-dock are also taken into account. As a first objective, the proposed model attempts to minimize the total operation time, and as a second objective, it aims to manage the equipment and manpower required in the cross-docking terminal by minimizing the number of doors involved in unloading and loading operations. Considering the uncertainty of the parameters, triangular fuzzy numbers are used to deal with the uncertainty, and a hybrid solution approach is developed for solving multi-objective possibilistic programming problems. The proposed model and solving approach are used for scheduling incoming and outgoing trucks at a cross-docking terminal as part of a food and beverage-producing group, and the results are compared with two existing methods. The results show that the proposed method performs better compared to existing methods

Energy resources are one of the most important factors and elements of sustainable development in any country. Therefore, according to the increasing need of countries for development, the amount of use of renewable energies has been increasing, so that one of the indicators of development is energy consumption. One of the processes that can be effective in any country to consider this importance and apply it to all work processes is supply chain management. Considering the importance of this issue, in the present research, an effort has been made to model the supply chain and decision-making at the level of macro-planning, taking into account the three dimensions of economic, social and environmental sustainability. The basis of this research is a mathematical programming approach and a method for modeling the renewable energy supply chain. An attempt has been made to model by considering the dynamics of valuation of indicators in the form of a supply chain and by solving the model using Lingo software, we can achieve a more stable solution at the planning level of the supply chain. Considering the capability of the process, as a quality criterion in the evaluation process of renewable energy indicators, as well as valuing the indicators in the first stage with the help of the data envelopment analysis, are innovations of this model. The results of solving this problem are a set of indicators that according to the conditions of the problem and the importance of each indicator in each layer of the supply chain, the most important ones are selected and applied to develop a suitable strategic plan framework for the development of this type of energy in the country.

In today's competitive world, supply management plays a significant role in achieving an efficient supply chain. One of the most important goals of supply management is to select sustainable suppliers and determine the optimal order allocated to suppliers. The process of selecting a sustainable supply begins with the determination of the criteria which are effective on the decision. Considering that the importance of all these criteria is not the same for organizations, multi-criteria decision-making methods are used to determine the weights of these critera. In this paper, three methods of Fuzzy DEMATEL, combination of analytical network process method and fuzzy DEMATEL type 1 and combination of analytic network process method and Fuzzy DEMATEL type 2 are used to determine the weights of effective criteria. Also, to determine the scores of suppliers, the innovative combined approach of fuzzy Taguchi loss function and fuzzy method of similarity to the ideal solution is used. In the hybrid approach, first, experts give scores to suppliers for their performance in different political, economic, social conditions, and based on this, the fuzzy Taguchi loss function is calculated. Considering that the loss function has a negative charge, the Taguchi loss functions are inverted and used as the input of the fuzzy TOPSIS method. In this paper, the sensitivity of the mentioned multi-criteria decision-making methods in calculating the weights of the criteria is examined with different conditions. The scores of suppliers are calculated based on their performances in the worst, normal and best conditions.

Today, the diversity of customer orders, development of management information systems, competition in the global environment, and expanding public awareness have led companies to focus on supply chain management. In addition to economic considerations, environmental issues such as climate change and greenhouse gas emissions, as well as social concerns such as workers' and employees' rights, have become important aspects of supply chain management. Sustainable supply chains aim to optimize supply chain management in three different areas: economic, social, and environmental. This research focuses on the sustainable evaluation and selection of suppliers in Shadshir dairy company. First, suitable criteria were identified through a comprehensive literature review. Second, the decision team was asked to determine the importance and relevance of each criterion. Fuzzy DEMATEL was applied to determine the weights of the criteria, and fuzzy VIKOR was used to evaluate suppliers. Finally, a sensitivity analysis was conducted on some important parameters. The results show that the economic and environmental criteria are the most important aspects of the supplier selection problem.

Maintenance is one of the basic concepts in state of-the-art organizations. the main objectives of Maintenance, is increasing equipment life-span, reducing costs, and augmenting machinery productivity. Achieving these things by the lean processes is faster. In this research, a study was conducted on industry documents and literature review, according to these documents and the opinion of academic experts, an open questionnaire was designed and provided to industry experts and staff, the number of which reached 10 people and all of them had knowledge. Sufficient and necessary of the industry were located and the Internal Factor Evaluation (IFE) Matrix in the maintenance area of the industry were determined. According to the information obtained and also the literature review, a model was presented to respond to the identified weaknesses. which steps are realized through 6 steps: (1) notification of Maintenance (2) selection and prioritization, (3) planning, (4) timing, (5) execution, and (6) performance inspection. Then, in order to check or not to confirm the non-approval of the classification of identified weaknesses in order to integrate the steps of the proposed model by experts and projects, other questionnaires and using the kappa coefficient of the steps of the proposed model in the industry. Have been cut. Then, by holding training workshops and storm meetings, planning to respond to the identified damages, implementing high-urgency operational plans, he thought of reducing the compressor preventive network program by 40% in the standard 8-month period. Production of the number of people in the forklift repair department.