rss_2.0Sciendo RSS Feed for Foundations of Computing and Decision Scienceshttps://sciendo.com/journal/FCDShttps://www.sciendo.comhttps://sciendo-parsed.s3.eu-central-1.amazonaws.com/6471cc0d215d2f6c89db1379/cover-image.jpghttps://sciendo.com/journal/FCDS140216https://sciendo.com/article/10.2478/fcds-2023-0017<abstract> <title style='display:none'>Abstract</title> <p>Adequate and desirable connections between suppliers and customers necessitate an appropriate flow of information. Therefore, a promising and proper data collaboration in the supply chain is of tremendous significance. Thus, the study’s main objective is to provide multiple objective programming models under uncertain conditions to assess the performance of suppliers. To meet that aim, a case study for the reliability assessment of the presented model is carried out. That section is associated with supply chain visibility (SCV). Likewise, the likelihood of unpredicted and undesirable incidents involving supply chain risk (SCR) is taken into consideration. The intimate relation between visibility and risk of the supply chain is deemed efficient for the performance of the supply chain. Incoherence in maximization and minimization of SCR and SCV and other factors, including costs, capacity, or demand, necessitates multiple objective programming models to assess suppliers’ performance to accomplish the before-mentioned aims. The study’s results indicate the high reliability of the proposed model. Besides, the numeral results reveal that decision-makers in selecting suppliers mainly decrease SCR and then attempt to enhance SCV. In conclusion, the provided model in the study can be a desirable model for analyzing and estimating supplier performance with SCR and SCV simultaneously.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00172023-10-05T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0012<abstract> <title style='display:none'>Abstract</title> <p>In this paper, we have done a rapid and very simple algorithm that resolves the multiple objective combinatorial optimization problem. This, by determining a basic optimal solution, which is a strong spanning tree constructed, according to a well-chosen criterion. Consequently, our algorithm uses notions of Bellman’s algorithm to determine the best path of the network, and Ford Fulkerson’s algorithm to maximise the flow value. The Simplex Network Method that permits to reach the optimality conditions manipulates the two algorithms. In short, the interest of our work is the optimization of many criteria taking into account the strong spanning tree, which represents the central angular stone of the network. To illustrate that, we propose to optimize a bi-objective distribution problem.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00122023-10-05T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0011<abstract> <title style='display:none'>Abstract</title> <p>This paper proposes a mathematical model of Sustainable Closed-Loop Supply Chain Networks (SCLSCNs). When an outbreak occurs, environmental, economic, and social aspects can be traded off. A novelty aspect of this paper is its emphasis on hygiene costs. As well as healthcare education, prevention, and control of COVID-19, this model offers job opportunities related to COVID-19 pandemic. COVID-19 damages lead to lost days each year, which is one of the negative social aspects of this model. COVID-19 was associated with two environmental novelties in this study. positive and negative effects of COVID-19 can be observed in the environmental context. As a result, there has been an increase in medical waste disposal and plastic waste disposal. Multi-objective mathematical modeling whit Weighted Tchebycheff method scalarization. In this process, the software Lingo is used. The COVID-19 pandemic still has a lot of research gaps because it’s a new disease. An SC model that is sustainable and hygienic will be developed to fill this gap in the COVID-19 condition disaster. Our new indicator of sustainability is demonstrated using a mixed-integer programming model with COVID-19-related issues in a Closed-Loop Supply Chain (CLSC) overview.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00112023-10-05T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0016<abstract> <title style='display:none'>Abstract</title> <p>This study examines the issue of distribution network design in the supply chain system. There are many production factories and distribution warehouses in this issue. The most efficient strategy for distributing the product from the factory to the warehouse and from the warehouse to the customer is determined by solving this model. This model combines location problems with and without capacity limits to study a particular location problem. In this system, the cost of production and maintenance of the product in the factory and warehouse is a function of its output. This increases capacity without additional costs, and ultimately does not lose customers. This algorithm is a population-based, innovative method that systematically combines answers to obtain the most accurate answer considering quality and diversity. A two-phase recursive algorithm based on a scattered object has been developed to solve this model. Numerical results show the efficiency and effectiveness of this two-phase algorithm for problems of different sizes.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00162023-10-05T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0014<abstract> <title style='display:none'>Abstract</title> <p>Locating facilities such as factories or warehouses is an important and strategic decision for any organization. Transportation costs, which often form a significant part of the price of goods offered, are a function of the location of the plans. To determine the optimal location of these designs, various methods have been proposed so far, which are generally definite (non-random). The main aim of the study, while introducing these specific algorithms, is to suggest a stochastic model of the location problem based on the existing models, in which random programming, as well as programming with random constraints are utilized. To do so, utilizing programming with random constraints, the stochastic model is transformed into a specific model that can be solved by using the latest algorithms or standard programming methods. Based on the results acquired, this proposed model permits us to attain more realistic solutions considering the random nature of demand. Furthermore, it helps attain this aim by considering other characteristics of the environment and the feedback between them.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00142023-10-05T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0013<abstract> <title style='display:none'>Abstract</title> <p>Recently, air pollution has received much attention as a result of reflections on environmental issues. Accordingly, the hub location problem (HLP) seeks to find the optimal location of hub facilities and allocate points for them to meet the demands between source-destination pairs. Thus, in this study, decisions related to location and allocation in a hub network are reviewed and a multi-objective model is proposed for locating and allocating capacity-building facilities at different time periods over a planning horizon. The objective functions of the model presented in this study are to minimize costs, reduce air pollution by diminishing fuel consumption, and maximize job opportunities. In order to solve the given model, the General Algebraic Modeling System (GAMS) along with innovative algorithms are utilized. The results presented a multi-objective sustainable model for full-covering HLP, and provided access to a hub network with minimum transport costs, fuel consumption, and GHG (greenhouse gas) emissions, and maximum job opportunities in each planning horizon utilizing MOICA (multi-objective imperialist competitive algorithm) and GAMS to solve the proposed model. The study also assessed the performance of the proposed algorithms with the aid of the QM, MID, SM, and NSP indicators, acquired from comparing the proposed meta-heuristic algorithm based on some indicators, proving the benefit and efficiency of MOICA in all cases.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00132023-10-05T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0015<abstract> <title style='display:none'>Abstract</title> <p>Supply chains are one of the key tools in optimizing production and distribution simultaneously. However, information uncertainty is always a challenge in production and distribution management. The main purpose of this paper is to design a two-echelon supply chain in a multi-cycle state and in conditions of demand uncertainty. The task includes determining the number and location of distribution centers, planning capacity for active distribution centers, and determining the amount of shipments between different levels so that the total costs of the chain are minimized. Uncertainty is applied through discrete scenarios in the model and the problem is formulated by multi-stage stochastic programming method in the form of a mixed integer linear model. The results acquired using two indicators called VMS and VSS demonstrated that modeling the supply chain design problem with the multi-stage stochastic approach can result in significant costs reduction. Plus, utilizing mathematical expectation can generate misleading results, therefore resulting in the development of supply chain designs incapable of satisfying demand due to its overlooked limitations.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00152023-10-05T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0006<abstract> <title style='display:none'>Abstract</title> <p>Criteria weighting is a widely used and also an important feature of multi criteria decision making problems specially in engineering, computer science and management investigations. In particular in many studies related to complex systems there would be usually two main groups of cause and effect criteria. In this research it is intended to make an hybrid objective model comprising DEMATEL and SWARA techniques to assign classified weights to the subgroup of cause and effect criteria. As a main goal, the proposed hybrid model in this presented paper can afford to assign greater values for criteria who belong to cause group. In this regard we apply the objective information which derived from the parameters of (R, equal to sum of direct and indirect influence of a criteria), (R/C, named as net influence power of a criteria) and (R-C, named as net effect of a criteria) related to the final total influence matrix T in DEMATEL methodology. The main contribution in this work lies in utilizing the SWARA methodology and making us of its revision where the relatively Comparative Importance <italic>S_j</italic>, applied in SWARA technique is reconfigured by some aggregation operators including <italic>max</italic>, <italic>Einstein</italic> and <italic>Hamacher</italic> operators for obtaining more uniformed weights of cause and effect criteria relatively to SWARA basic methodology. Finally results shows that the (R/C) and (R-C)would transfer more clear and refined data and numeric information achieving better and highly reliable weights of criteria categorized into two groups of cause and effect group.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00062023-06-30T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0007<abstract> <title style='display:none'>Abstract</title> <p>Smart cities are included in the literature as a technology-based concept that has been on the agenda in recent years and whose framework is constantly changing with the changes in technology. There are different frameworks and indexes to define the smartness of a city. Smart City Index 2021 published by Institute for Management Development (IMD) and Singapore University of Technology and Design (SUTD) is one of the accepted studies in the world. In the report of Smart City Index 2021, 118 cities are evaluated in five criteria namely health &amp; safety, mobility, activities, opportunities (work &amp; school) and governance. To re-evaluate the cities and compare the results, a Multi-Criteria Decision Making (MCDM) process including Entropy based Complex Proportional Assessment (COPRAS) and Addivite Ratio Assessment (ARAS) methodology is applied in this paper. To prioritize the criteria, entropy weight method is used. 118 cities are ranked both technologically and structurally using the COPRAS and ARAS method. As a result of the analyses, according to these methods, the rankings of the smart cities are the same. Also, when technologically smart cities are listed, it is determined that the first three countries are Zhuhai, Shenzhen, Nanjing, and at the same time, Abu Dhabi, Chongqing, Hangzhou in terms of structurally.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00072023-06-30T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0009<abstract> <title style='display:none'>Abstract</title> <p>In the era of internet access, recommender systems try to alleviate the difficulty consumers face while trying to find items (e.g. services, products, or information) that better match their needs. To do so, a recommender system selects and proposes (possibly unknown) items that may be of interest to some candidate consumer, by predicting her/his preference for this item. Given the diversity of needs between consumers and the enormous variety of items to be recommended, a large set of approaches have been proposed by the research community. This paper provides a review of the approaches proposed in the entire research area of content-based recommender systems, and not only in one part of it. To facilitate understanding, we provide a categorization of each approach based on the tools and techniques employed, which results to the main contribution of this paper, a content-based recommender systems taxonomy. This way, the reader acquires a quick and complete understanding of this research area. Finally, we provide a comparison of content-based recommender systems according to their ability to efficiently handle well-known drawbacks.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00092023-06-30T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0010<abstract> <title style='display:none'>Abstract</title> <p>Differential evolution algorithm (DE) is a well-known population-based method for solving continuous optimization problems. It has a simple structure and is easy to adapt to a wide range of applications. However, with suitable population sizes, its performance depends on the two main control parameters: scaling factor (<italic>F</italic> ) and crossover rate (<italic>CR</italic>). The classical DE method can achieve high performance by a time-consuming tunning process or a sophisticated adaptive control implementation. We propose in this paper an adaptive differential evolution algorithm with a pheromone-based learning strategy (ADE-PS) inspired by ant colony optimization (ACO). The ADE-PS embeds a pheromone-based mechanism that manages the probabilities associated with the partition values of <italic>F</italic> and <italic>CR</italic>. It also introduces a resetting strategy to reset the pheromone at a specific time to unlearn and relearn the progressing search. The preliminary experiments find a suitable number of subintervals (<italic>ns</italic>) for partitioning the control parameter ranges and the reset period (<italic>rs</italic>) for resetting the pheromone. Then the comparison experiments evaluate ADE-PS using the suitable <italic>ns</italic> and <italic>rs</italic> against some adaptive DE methods in the literature. The results show that ADE-PS is more reliable and outperforms several well-known methods in the literature.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00102023-06-30T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0008<abstract> <title style='display:none'>Abstract</title> <p>Social media are a rich source of user generated content where people express their views towards the products and services they encounter. However, sentiment analysis using machine learning models are not easy to implement in a time and cost effective manner due to the requirement of expert human annotators to label the training data. The proposed approach uses a novel method to remove the neutral statements using a combination of lexicon based approach and human effort. This is followed by using a deep active learning model to perform sentiment analysis to reduce annotation efforts. It is compared with the baseline approach representing the neutral tweets also as a part of the data. Considering brands require aspect based ratings towards their products or services, the proposed approach also categorizes predicting ratings of each aspect of mobile device.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00082023-06-30T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0003<abstract> <title style='display:none'>Abstract</title> <p>With a large variety of communication methods and protocols, many software architects face the problem of choosing the best way for services to share information. For communication technology to be functional and practical, it should enable developers to define a complete set of CRUD methods for the processed data. The research team compared this paper’s most commonly used data transfer protocols and concepts: REST, WebSocket, gRPC GraphQL and SOAP. A set of web servers was implemented in Python, each using one of the examined technologies. Then, the team performed an automated benchmark measuring time and data transfer overhead for a set of defined operations: creating an entity, retrieving a list of 100 entities and fetching details of one entity. Tests were designed to avoid the results being interfered with by database connection or docker-compose environment characteristics. The research team has concluded that gRPC was the most efficient and reliable data transfer method. On the other hand, GraphQL turned out to be the slowest communication method of all. Moreover, its server and client libraries caused the most problems with proper usage in a web server. SOAP did not participate in benchmarking due to limited compatibility with Python and a lack of popularity in modern web solutions.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00032023-03-19T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0004<abstract> <title style='display:none'>Abstract</title> <p>Software requirements specification is an important foundation of the software development process. It documents the requirements, expectations, and restrictions for a system to be developed. It should describe what the produced system will offer in detail and unambiguously. It should also provide a realistic basis for estimating product costs, risks, and schedules. Still, it is difficult to prepare a useful specification effectively. We want to propose an approach to creating a good specification. We started the work from scratch by determining what the scope of the specification should be. We asked people who work on IT projects what information is and should be included in the specifications with which they work. This paper presents results from a survey conducted with 163 participants who have experience working on commercial software development projects. The main observation is that the content of requirements specification differs with respect to project characteristics, such as industry or financing method. We also noticed that the information about integration with external systems and functionalities most often appears in the SRS.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00042023-03-19T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0005<abstract> <title style='display:none'>Abstract</title> <p>Since the collapse of the Soviet Bloc, Polish researchers in the software engineering area made a large e ort to close the gap developed during the times of the Iron Curtain and the ensuing limited access to Western technology. The question arises as to whether they eventually managed to attain – or maybe even to surpass the scientific output in this area of the developed Western countries. In this paper, we perform analysis on papers published in 16 high-quality software engineering journals within the last 30 years to measure the Polish contribution to the global scientific output in the area of software engineering. We observe how the Polish contribution changed in quantity in relation to the global scientific output in subsequent years. We also identify the journals that attracted the Polish authors the most, the institutions located in Poland that contributed the most, as well as the most productive Polish authors and the most acknowledged works (in terms of citation number) written by Polish authors. Moreover, we investigate the topics most often chosen by them.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00052023-03-19T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0001<abstract> <title style='display:none'>Abstract</title> <p>Cognitive biases influence every human being, including the individuals that take part in the software development process. Fixation is a cognitive bias that occurs when one focuses too much on certain items, events, obstacles or activities. In this study, we examine whether agile team members fixate on any particular agile practices. Through a set of semi-structured interviews, we investigated the source of these fixations, their consequences, and then propose possible countermeasures. We found that practitioners tend to fixate on practices that give them a sense of being in control over the project (such as meetings or Scrum events), while neglecting the Agile Principles of self-organising teams and working at a sustainable pace. This resulted in a series of problems, such as futile attempts to control team members, oversharing information with the client, meetings becoming a form of interrogation, and others.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00012023-03-19T00:00:00.000+00:00https://sciendo.com/article/10.2478/fcds-2023-0002<abstract> <title style='display:none'>Abstract</title> <p>Source code understandability is a desirable quality factor affecting long-term code maintenance. Understandability of source code can be assessed in a variety of ways, including subjective evaluation of code fragments (perceived understandability), correctness, and response time to tasks performed. It can also be assessed using various source code metrics, such as cyclomatic complexity or cognitive complexity. Programming languages are evolving, giving programmers new ways to do the same things, e.g., iterating over collections. Functional solutions (lambda expressions and streams) are added to typical imperative constructs like iterators or <italic>for-each</italic> statements. This research aims to check if there is a correlation between perceived understandability, understandability measured by task correctness, and predicted by source code metrics for typical tasks that require iteration over collections implemented in Java. The answer is based on the results of an experiment. The experiment involved 99 participants of varying ages, declared Java knowledge and seniority measured in years. Functional code was perceived as the most understandable, but only in one case, the subjective assessment was confirmed by the correctness of answers. In two examples with the highest perceived understandability, streams received the worst correctness scores. Cognitive complexity and McCabe’s complexity had the lowest values in all tasks for the functional approach, but – unfortunately – they did not correlate with answer correctness. The main finding is that the functional approach to collection manipulation is the best choice for the filter-map-reduce idiom and its alternatives (e.g., filter-only). It should not be used in more complex tasks, especially those with higher complexity metrics.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/fcds-2023-00022023-03-19T00:00:00.000+00:00https://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+00:00https://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+00:00https://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+00:00en-us-1