rss_2.0Foundations of Computing and Decision Sciences FeedSciendo RSS Feed for Foundations of Computing and Decision Scienceshttps://sciendo.com/journal/FCDShttps://www.sciendo.comFoundations of Computing and Decision Sciences Feedhttps://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/6398dd1db460d8681e76959a/cover-image.jpghttps://sciendo.com/journal/FCDS140216Optimizing the Interaction Between Two Closed-Loop Supply Chains Based on Inverse Logistics Using the Game Theory Methodhttps://sciendo.com/article/10.2478/fcds-2022-0025<abstract> <title style='display:none'>Abstract</title> <p>Over the past few years, attention to environmental problems, legal necessities, and economic advantages emerging from reproduction activities has attracted attention to reverse logistics activities in the form of a closed-loop supply chain, whether in industry or scientific research. The current study aims to model competitiveness and comparison between two closed-loop three-level supply chains, each of which includes a manufacturer, a retailer, and a third party to collect the products used by the customer, taking into account the concepts of game theory and the existence of aggregates. Moreover, a separate supplier for each chain is considered. In the forward supply chain, the manufacturer produces new products using new components or re-used products that have been collected from the consumer, then sells these products mainly to the retailer, and the retailer sells them. In the reverse chain, the collector provides the used products to the manufacturer after collection. The study utilized the definitions and concepts of game theory to model this closed loop chain as a Stackelberg game to obtain the optimal value of wholesale and retail price and the optimal value of the product return coefficient for the collector. Finally, the models based on some numerical examples are solved. Given the results, the remanufacturing costs have a significant role in making more profits for all members in such chains, and competitive chains should attempt to remanufacture the products at lower costs.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00252022-12-13T00:00:00.000+00:00Design a Mathematical Planning Approach to Optimize the Supply Chain Taking Into Account Uncertainties In Distributorshttps://sciendo.com/article/10.2478/fcds-2022-0022<abstract> <title style='display:none'>Abstract</title> <p>With the globalization of markets and increasing competition in global markets, the attempts of organizations to survive in this market has increased and has resulted in the emergence of the philosophy of Supply Chain Management. There is uncertainty in the reliability of supply chain facilities for reasons such as natural disasters, terrorist attacks, labor errors, and weather conditions. Therefore, when making strategic decisions, the system will continue to operate with minimal damage. Over the course of this study, the uncertainty of supplier layers in the supply chain has been modeled. To meet that aim, the issue of supply chain, including producers, warehouses, suppliers and consumers are considered. To calculate the cost of breakdowns due to the non-functioning of distributors, the scenario-building method has been utilized. Finally, the desired model is solved with Gomez software and the results are presented. The result of the study demonstrate the efficiency of this model in the facility location decision-making in supply chains.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00222022-12-13T00:00:00.000+00:00An Introduction to the Special Issue “Recent advances on supply chain network design”https://sciendo.com/article/10.2478/fcds-2022-0017<abstract> <title style='display:none'>Abstract</title> <p>Discussions of the resiliency, sustainability, and agility of supply chains are important in the research and management of supply chains in these difficult times, considering the ongoing pandemic of COVID-19. A viable supply chain is often characterized by resiliency, sustainability, and agility in its network design. Resiliency is essential because disruption and demand fluctuations are forced upon SCs, and the effects of these for many managerial supply chains are unknown. In addition, applying novel technology in the supply chain, such as blockchain, Internet-of-Things (IoT), and artificial intelligence (AI) as agility tools can assist and enable the transition to lean production. This special issue of the Foundations of Computing and Decision Sciences is dedicated to advancements in this fields. Besides, the special issue covers instructional information about OR techniques which are useful for addressing real-world applications on such challenges.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00172022-12-13T00:00:00.000+00:00Integrated Pricing and Inventory Control for Perishable Products, Taking into Account the Lack of Backlog and Inventory Management Policy by the Sellerhttps://sciendo.com/article/10.2478/fcds-2022-0020<abstract> <title style='display:none'>Abstract</title> <p>Recently, utilizing appropriate inventory control policy and determining the optimal selling price for various goods has been the main topic of scientific and industrial research. Inventory management policy 1 by the seller is one solution that improves the chain’s performance by creating coordination between members of the supply chain. The current study attempts to devise an integrated model of inventory pricing and control under the inventory management policy by the seller for perishable goods with shortages is considered. The purpose of presenting the model is to determine the optimal price, the optimal repayment time, and the order size, in order to maximize the profit. To acquire those optimal values, the profit functions of the buyer and the seller are taken into account. Given the results acquired, it is demonstrated that at any cost, the repayment time is unique and optimal. It is concluded that with the optimal recovery time available, the objective function is a concave function of price, and its optimal value is available. Furthermore, utilizing the inventory management policy by the seller could be a proper means to reducing retailer costs while raising their profit.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00202022-12-13T00:00:00.000+00:00Introduce a New Mathematical Approach to Inventory Management in Production Processes Under Constrained Conditionshttps://sciendo.com/article/10.2478/fcds-2022-0023<abstract> <title style='display:none'>Abstract</title> <p>Nowadays, some manufacturing organizations may well face production restrictions. For example, in case the number of products goes up, the company might not be capable of producing all products. As a consequence, the company may face backlogging. In the meanwhile, in case the demand for products rises, the given company may experience a restricted capacity to react to that kind of demand properly; thus, it will suffer backlogging. Over the course of this study, that kind of company facing the mentioned circumstances is considered. To meet those exceeded demands, companies would be forced to purchase some products from outside. Thus, the study’s primary aim is to define and calculate the optimum make and buy a number of products so that overall inventory cost is reduced and optimized. To do so, a model is proposed referred to as the make-with-buy model. This model is designed and solved by exact solution software in the based branch and bound method. The results of the study confirm the feasibility and efficiency of this method and demonstrate that this model can be applied to lessen the overall inventory costs, including maintenance, order, setup, and purchasing costs, and also the total costs of products.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00232022-12-13T00:00:00.000+00:00A New Wooden Supply Chain Model for Inventory Management Considering Environmental Pollution: A Genetic algorithmhttps://sciendo.com/article/10.2478/fcds-2022-0021<abstract> <title style='display:none'>Abstract</title> <p>Nowadays, companies need to take responsibility for addressing growing markets and the growing expectations of their customers to survive in a highly competitive context that is progressing on a daily basis. Rapid economic changes and increasing competitive pressure in global markets have led companies to pay special attention to their supply chains. As a result, in this research, a mathematical model is proposed to minimize closed loop supply chain costs taking into account environmental effects. Thus, suppliers first send wood as raw materials from forests to factories. After processing the wood and turning it into products, the factories send the wood to retailers. The retailers then send the products to the customers. Finally, customers send returned products to recovery centers. After processing the products, the recovery centers send their products to the factories. The considered innovations include: designing a supply chain of wood products regarding environmental effects, customizing the genetic solution approach to solve the proposed model 3-Considering the flow of wood products and determining the amount of raw materials and products sent and received.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00212022-12-13T00:00:00.000+00:00Performance Measurement of the Sustainable Supply Chain During the COVID-19 Pandemic: A real-life case studyhttps://sciendo.com/article/10.2478/fcds-2022-0018<abstract> <title style='display:none'>Abstract</title> <p>This paper aims to introduce a framework to measure the sustainable performance of the supply chain (SC) during the COVID-19 pandemic. The SC stakeholders in this investigation are Suppliers, Production / Remanufacturing / Refurbishing Centers (Factories), Collection / Distribution Centers, Recycling / Landfill Centers, and Customers. The suggested sustainable supply chain (SSC) performance measurement included three pillars with 23 indicators. To evaluate the overall sustainability of the SC understudy, a composite index has been developed that combines all the indicators to reflect the sustainability performance of the SC. Four steps are involved in creating a composite index:1) measuring the value of indicators, 2) weighing indicators, 3) Using the normalization technique, and 4) Evaluating the overall SSC indicator. The real case in Iran is selected as an illustrative case. Our research contributions are: We suggested a novelty indicator of SSC to better show the economic, environmental, and social tradeoffs during the COVID-19 pandemic and lockdowns. We have found and measured the negative and positive impacts of COVID-19 on aspects of sustainability in SC. Based on the achieved data of the real case study, a numerical example is represented to explain how to calculate the composite index. The main contribution of this paper is the development of SSC indicators during the COVID-19 epidemic.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00182022-12-13T00:00:00.000+00:00Planning the location of facilities in the supply chain using the firefly meta-innovation algorithmhttps://sciendo.com/article/10.2478/fcds-2022-0024<abstract> <title style='display:none'>Abstract</title> <p>Analysis of supply chain location issues and decision-making regarding the location of facilities in the supply chain is one of the most important issues in the decision-making of governments, organizations and companies. Undoubtedly, the correct location of facilities has very important effects on economic benefits, providing appropriate services and customer satisfaction. Supply chain issue is one of the most widely used issues in today’s competitive world and location issues are among the most used issues in designing supply chain networks to improve and reduce costs and increase competitiveness. The facilities under consideration include warehouses and distribution centers, which have been solved with the aim of reducing transportation costs. And then the two methods are compared. The problem is solved in small, medium and large dimensions and finally it was concluded that the firefly algorithm had a better performance than the genetic algorithm.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00242022-12-13T00:00:00.000+00:00A Mathematical Model for the Vehicles Routing Problem with Multiple Depots, Considering the Possibility of Return Using the Tabu Search Algorithmhttps://sciendo.com/article/10.2478/fcds-2022-0019<abstract> <title style='display:none'>Abstract</title> <p>The current study examines an essential type of vehicle routing problem (VRP). This type is one where customers are served by limited-capacity vehicles from multiple depots and is known as Multi-Depot Capacitated Vehicle Routing Problem (MDCVRP). The novelty of this study is that in the present case, cars, after Leaving the Depot, can go back to any other depot. Those issues seem to occur in most real-world issues where information, messages, or news are sent electronically from somewhere. The purpose of the problem is to minimize the costs associated with routing. Regarding the literature on such issues, it has been proven in previous studies and research that these problems are among the hard-NP problems, and to solve them using the metaheuristic method, the exact methods justify it. After changing the basic model, this study developed a Tabu Search (TS) algorithm. The study results demonstrate that if the equipment can return to any depot, the cost is significantly reduced in contrast to the case where equipment is forced to return to their depot.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00192022-12-13T00:00:00.000+00:00Green Manufacturing: An Assessment of Enablers’ Framework Using ISM-MICMAC Analysishttps://sciendo.com/article/10.2478/fcds-2022-0015<abstract> <title style='display:none'>Abstract</title> <p>Manufacturing is one of the biggest drivers of a country’s economic growth. Nevertheless, due to globalization and flourishing consumer markets, the technological influx in manufacturing evolution poses a significant threat to climate change. To deal with the situation, green manufacturing came forward to play a vital role in lowering the impact of mass production on the global environment. The qualitative research based on expert opinion is used to have viewpoints for the implementation of green manufacturing based on green supply chain manufacturing (GSCMEs) enablers. The study, in this regard, focuses on exploring the key enablers adopted by the manufacturers to embrace green practices by using framework based on Interpretative Structural Modelling and Cross-Impact Multiplication Applied to Classification (MICMAC) analysis. Results indicate that economic constraints and the regulatory framework have high driving power and less dependency power. Researchers provide managers with a new outlook on the future towards building an eco-friendly supply chain and gaining a competitive edge over their competitors.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00152022-10-08T00:00:00.000+00:00On Solving 0/1 Multidimensional Knapsack Problem with a Genetic Algorithm Using a Selection Operator Based on K-Means Clustering Principlehttps://sciendo.com/article/10.2478/fcds-2022-0014<abstract> <title style='display:none'>Abstract</title> <p>The growing need for profit maximization and cost minimization has made the optimization field very attractive to both researchers and practitioners. In fact, many authors were interested in this field and they have developed a large number of optimization algorithms to solve either academic or real-life problems. Among such algorithms, we cite a well-known metaheuristic called the genetic algorithm. This optimizer tool, as any algorithm, suffers from some drawbacks; like the problem of premature convergence. In this paper, we propose a new selection strategy hoping to avoid such a problem. The proposed selection operator is based on the principle of the k-means clustering method for the purpose of guiding the genetic algorithm to explore different regions of the search space. We have elaborated a genetic algorithm based on this new selection mechanism. We have then tested our algorithm on various data instances of the 0/1 multidimensional knapsack problem. The obtained results are encouraging when compared with those reached by other versions of genetic algorithms and those reached by an adapted version of the particle swarm optimization algorithm.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00142022-10-08T00:00:00.000+00:00Epidemiology-constrained Seating Plan Problemhttps://sciendo.com/article/10.2478/fcds-2022-0013<abstract> <title style='display:none'>Abstract</title> <p>The emergence of an infectious disease pandemic may result in the introduction of restrictions in the distance and number of employees, as was the case of COVID-19 in 2020/2021. In the face of fluctuating restrictions, the process of determining seating plans in office space requires repetitive execution of seat assignments, and manual planning becomes a time-consuming and error-prone task. In this paper, we introduce the Epidemiology-constrained Seating Plan problem (ESP), and we show that it, in general, belongs to the NP-complete class. However, due to some regularities in input data that could a affect computational complexity for practical cases, we conduct experiments for generated test cases. For that reason, we developed a computational environment, including the test case generator, and we published generated benchmarking test cases. Our results show that the problem can be solved to optimality by CPLEX solver only for specific settings, even in regular cases. Therefore, there is a need for new algorithms that could optimize seating plans in more general cases.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00132022-10-08T00:00:00.000+00:00Ontology-Based Semantic Checking of Data in Railway Infrastructure Information Systemshttps://sciendo.com/article/10.2478/fcds-2022-0016<abstract> <title style='display:none'>Abstract</title> <p>Semantic checking of railway infrastructure information support data is one of the ways to improve the consistency of information system data and, as a result, increase the safety of train traffic. Existing ontological developments have demonstrated the applicability of description logic for modelling railway transport, but have not paid enough attention to the data resources structure and the railway regulatory support. In this work, the formalization of the tabular presentation of data and the rules of railway transport regulations is carried out using the example of a connection track passport and temporary speed restrictions using ontological means, data wrangling and extraction tools. Ontologies of the various formats data resources and railway station infrastructure, tools for converting and extracting data have been developed. The semantic checking of the compliance of railway information system data with regulatory documents in terms of the connection track passport is carried out on the basis of a multi-level concretization model and integration of ontologies. The mechanisms for implementing the constituent ontologies and their integration are demonstrated by an example. Further research includes ontological checking of natural language normative documents of railway transport.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00162022-10-08T00:00:00.000+00:00Developing a Mathematical Model for a Green Closed-Loop Supply Chain with a Multi-Objective Gray Wolf Optimization Algorithmhttps://sciendo.com/article/10.2478/fcds-2022-0007<abstract> <title style='display:none'>Abstract</title> <p>Intense competition in today’s market and quick change in customer preferences, along with the rapid development of technology and globalization, have forced companies to work as members of a supply chain instead of individual companies. The success of the supply chain depends on the integration and coordination of all its institutions to form an efficient network structure. An efficient network leads to cost savings throughout the supply chain and helps it respond to customer needs faster. Accordingly, and with respect to the importance of the supply chain, in this study a developed mathematical model for the design of a green closed-loop supply chain is presented. In this mathematical model, the economic and environmental objectives are simultaneously optimized. In order to tackle this mathematical model, two methods of epsilon constraint and multi-objective gray wolf optimization (MOGWO) algorithm have been applied. The results of comparisons between the two mentioned methods show that MOGWO reduce the average solving time from about 1300 seconds to 88 seconds. In the last step of this research, in order to show the application of the proposed mathematical model and the method of solving the research problem, it was implemented in the supply chain of Dalan Kouh diary product and the Pareto optimal solutions were analyzed.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00072022-07-09T00:00:00.000+00:00Optimizing the Multi-Level Location-Assignment Problem in Queue Networks Using a Multi-Objective Optimization Approachhttps://sciendo.com/article/10.2478/fcds-2022-0010<abstract> <title style='display:none'>Abstract</title> <p>Using hubs in distribution networks is an efficient approach. In this paper, a model for the location-allocation problem is designed within the framework of the queuing network in which services have several levels, and customers must go through these levels to complete the service. The purpose of the model is to locate an appropriate number of facilities among potential locations and allocate customers. The model is presented as a multi-objective nonlinear mixed-integer programming model. The objective functions include the summation of the customer and the waiting time in the system and the waiting time in the system and minimizing the maximum possibility of unemployment in the facility. To solve the model, the technique of accurate solution of the epsilon constraint method is used for multi-objective optimization, and Pareto solutions of the problem will be calculated. Moreover, the sensitivity analysis of the problem is performed, and the results demonstrate sensitivity to customer demand rate. Based on the results obtained, it can be concluded that the proposed model is able to greatly summate the customer and the waiting time in the system and reduce the maximum probability of unemployment at several levels of all facilities. The model can also be further developed by choosing vehicles for each customer.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00102022-07-09T00:00:00.000+00:00Designing a Green Supply Chain Transportation System for an Automotive Company Based On Bi-Objective Optimizationhttps://sciendo.com/article/10.2478/fcds-2022-0011<abstract> <title style='display:none'>Abstract</title> <p>Recently, due to the increasing awareness of communities regarding environmental issues and environmental regulations, companies have evolved to provide products with lower prices and better quality to retain and attract customers. Economics should also pay attention to environmental goals. Therefore, it is essential to provide a supply chain model that can consider both economic and environmental objectives. In this paper, the green direct supply chain network is presented to an automotive company, including five suppliers, primary warehouses, manufacturing plants, distributors, and sales centers. The objectives of this model are to minimize the total cost of construction, transportation, and the amount of carbon dioxide emissions during forwarding network transportation at all levels. The proposed model is also drawn using the weight method, which is one of the methods for solving multi-objective problems, and the solution of the model part. Ultimately, it has been discussed how much the automobile company should focus on reducing carbon dioxide so that managers can determine the best solutions from the Pareto border according to their organization’s priorities, which can be environmental or financial.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00112022-07-09T00:00:00.000+00:00A New Model for Scheduling Operations in Modern Agricultural Processeshttps://sciendo.com/article/10.2478/fcds-2022-0008<abstract> <title style='display:none'>Abstract</title> <p>In recent years, the increase in population and the decrease in agricultural lands and water shortages have caused many problems for agriculture and farmers. That is why scheduling is so important for farmers. Therefore, the implementation of an optimal schedule will lead to better use of agricultural land, reduce water consumption in agriculture, increase efficiency and quality of agricultural products. In this research, a scheduling problem for harvesting agricultural products has been investigated. In this problem, there are n number of agricultural lands that in each land m agricultural operations are performed by a number of machines that have different characteristics. This problem is modeled as a scheduling problem in a flexible workshop flow environment that aims to minimize the maximum completion time of agricultural land. The problem is solved by programming an integer linear number using Gams software. The results show that the proposed mathematical model is only capable of solving small and medium-sized problems, and due to the Hard-NP nature of the problem, large-scale software is not able to achieve the optimal solution.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00082022-07-09T00:00:00.000+00:00Development of an Adaptive Genetic Algorithm to Optimize the Problem Of Unequal Facility Locationhttps://sciendo.com/article/10.2478/fcds-2022-0006<abstract> <title style='display:none'>Abstract</title> <p>The problem of unequal facility location involves determining the location of a set of production equipment whose dimensions are different, as well as the interrelationships between each of them. This paper presents an efficient method for optimizing the problem of unequal facility layouts. In this method, the genetic algorithm is improved and developed into an adaptive genetic algorithm. In this algorithm, the mutation operator is applied only when the similarity of chromosomes in each population reaches a certain level. This intelligence prevents jumps in situations where they are not needed and reduces computational time. In order to measure the performance of the proposed algorithm, its performance is compared with the performance of conventional genetic algorithms and refrigeration simulators. Computational results show that the adaptive genetic algorithm is able to achieve higher-quality solutions.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00062022-07-09T00:00:00.000+00:00The Main Trends and Challenges in The Development of the Different Industries During The COVID-19 Pandemichttps://sciendo.com/article/10.2478/fcds-2022-0012<abstract> <title style='display:none'>Abstract</title> <p>The purpose of the research in this article is to investigate the main trends in the development of the different industries during the COVID-19 pandemic, to identify the main problems facing the different industries in the context of the global crisis, as well as to form the basic concepts necessary for a real recovery of the global industry. The authors identify the main problems facing the aviation industry in the developing world crisis and possible ways to solve them. As a working hypothesis, it is proposed to form the basic concepts necessary for preparing and implementing operational measures to restore passenger and cargo aviation. Considering the main threats facing the aviation industry during COVID-19, the article proposes the organizational and economic mechanisms to restore the industry. Furthermore, several recovery scenarios are considered, considering the relevant factors that have a particular impact. Next, a novel mathematical model for pharmaceutical products, which are the most important in COVID-19 pandemics, is proposed. Moreover, the model considers the uncertainty, and a robust optimization approach is applied. The study is based on a comprehensive analysis of documentary data provided by government agencies in several European countries. An analysis of global and Russian passenger traffic for Q1-Q4 (quartile) of 2020 and a development forecast for Q1-Q2 of 2021 is provided. The scenario problems facing the aviation industry in the context of the COVID-19 crisis are identified. There are key concepts necessary to prepare and implement effective measures to restore the aviation industry.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00122022-07-09T00:00:00.000+00:00Design a Multi Period Closed-Loop Supply Chain Program to Supply Recycled Productshttps://sciendo.com/article/10.2478/fcds-2022-0009<abstract> <title style='display:none'>Abstract</title> <p>Over the course of the last decades, closed-loop supply chains (CLSC) and reverse logistics issues have attracted increasing attention owing to strict environmental laws, social responsibilities, economic interests, and customer awareness. Hence, the issue of closed-loop supply chain and reverse logistics has emerged as a field of research in the new era. This issue has received much attention because it allows recyclable products to return to their original cycle. Therefore, this study primarily intends to present a mathematical model for designing a supply chain network for recycled products. The multi-stage and multi-period objective function of the closed-loop supply chain is presented to meet that aim. In this chain, dismantling, recycling, and disposal centers are considered. The objective function is to reduce the total cost of the closed-loop supply chain. The results of optimizing the mathematical model demonstrate that this model has the necessary efficiency for use in recycled products.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2022-00092022-07-09T00:00:00.000+00:00en-us-1