Search results for: group problem solving (GPS)

Authors: Ekta Jain, Kalpana Dahiya, Vanita Verma

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This paper discusses a priority based imbalanced time minimization assignment problem dealing with the allocation of n jobs to m < n persons in which the project is carried out in two stages, viz. Stage-I and Stage-II. Stage-I consists of n1 ( < m) primary jobs and Stage-II consists of remaining (n-n1) secondary jobs which are commenced only after primary jobs are finished. Each job is to be allocated to exactly one person, and each person has to do at least one job. It is assumed that nature of the Stage-I jobs is such that one person can do exactly one primary job whereas a person can do more than one secondary job in Stage-II. In a particular stage, all persons start doing the jobs simultaneously, but if a person is doing more than one job, he does them one after the other in any order. The aim of the proposed study is to find the feasible assignment which minimizes the total time for the two stage execution of the project. For this, an iterative algorithm is proposed, which at each iteration, solves a constrained imbalanced time minimization assignment problem to generate a pair of Stage-I and Stage-II times. For solving this constrained problem, an algorithm is developed in the current paper. Later, alternate combinations based method to solve the priority based imbalanced problem is also discussed and a comparative study is carried out. Numerical illustrations are provided in support of the theory.

Keywords: assignment, imbalanced, priority, time minimization

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Authors: Debjani Chakraborty, Abhijit Chatterjee, Aishwaryaprajna

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Posynomials, a special type of polynomials, having singularities, pose difficulties while solving geometric programming problems. In this paper, a methodology has been proposed and used to obtain extreme values for geometric programming problems by nth degree polynomial interpolation technique. Here the main idea to optimise the posynomial is to fit a best polynomial which has continuous gradient values throughout the range of the function. The approximating polynomial is smoothened to remove the discontinuities present in the feasible region and the objective function. This spatial interpolation method is capable to optimise univariate and multivariate geometric programming problems. An example is solved to explain the robustness of the methodology by considering a bivariate nonlinear geometric programming problem. This method is also applicable for signomial programming problem.

Keywords: geometric programming problem, multivariate optimisation technique, posynomial, spatial interpolation

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Authors: Alberto Hananel

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The aim of this work is to modelize the occlusion of a person with temporomandibular disorders as an evolutionary equation and approach its solution by the construction and characterizing of discrete variational splines. To formulate the problem, certain boundary conditions have been considered. After showing the existence and the uniqueness of the solution of such a problem, a convergence result of a discrete variational evolutionary spline is shown. A stress analysis of the occlusion of a human jaw with temporomandibular disorders by finite elements is carried out in FreeFem++ in order to prove the validity of the presented method.

Keywords: approximation, evolutionary PDE, Finite Element Method, temporomandibular disorders, variational spline

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Authors: V. S. S. Kumar, B. Vikram

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The development of effective decision support tools that adopted in the construction industry is vital in the world we live in today, since it can lead to substantial cost reduction and efficient resource consumption. Solving the time-cost trade off problems and its related variants is at the heart of scientific research for optimizing construction planning problems. In general, the classical optimization techniques have difficulties in dealing with TCT problems. One of the main reasons of their failure is that they can easily be entrapped in local minima. This paper presents an investigation on the application of meta-heuristic techniques to two particular variants of the time-cost trade of analysis, the time-cost trade off problem (TCT), and time-cost trade off optimization problem (TCO). In first problem, the total project cost should be minimized, and in the second problem, the total project cost and total project duration should be minimized simultaneously. Finally it is expected that, the optimization models developed in this paper will contribute significantly for efficient planning and management of construction project.

Keywords: fuzzy sets, uncertainty, optimization, time cost trade off problems

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Authors: Lien-Fa Lin, Yung-Ming Li, Fu-Shun Hsieh

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With the advancement of information technology and development of group commerce, people have obviously changed in their lifestyle. However, group commerce faces some challenging problems. The products or services provided by vendors do not satisfactorily reflect customers’ opinions, so that the sale and revenue of group commerce gradually become lower. On the other hand, the process for a formed customer group to reach group-purchasing consensus is time-consuming and the final decision is not the best choice for each group members. In this paper, we design a social decision support mechanism, by using group discussion message to recommend suitable options for group members and we consider social influence and personal preference to generate option ranking list. The proposed mechanism can enhance the group purchasing decision making efficiently and effectively and venders can provide group products or services according to the group option ranking list.

Keywords: social network, group decision, text mining, group commerce

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Authors: A. M. Sagir

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The aim of this paper is to investigate the performance of the developed linear multistep block method for solving first order initial value problem of Ordinary Differential Equations (ODEs). The method calculates the numerical solution at three points simultaneously and produces three new equally spaced solution values within a block. The continuous formulations enable us to differentiate and evaluate at some selected points to obtain three discrete schemes, which were used in block form for parallel or sequential solutions of the problems. A stability analysis and efficiency of the block method are tested on ordinary differential equations involving practical applications, and the results obtained compared favorably with the exact solution. Furthermore, comparison of error analysis has been developed with the help of computer software.

Keywords: block method, first order ordinary differential equations, linear multistep, self-starting

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Authors: Vladyslav Povoroznyuk, Galina Dubetska, Roksolana Povoroznyuk

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In recent years, the problem of hyperuricemia is getting a particular importance due to its increased incidence in the world population. The aim of this study was to determine uriс acid level in blood serum, incidence of hyperuricemia among women in postmenopausal period and their association with body mass index and some components of metabolic syndrome (triglyceride, cholesterol, systolic and diastolic pressure). We examined 412 women in postmenopausal period. They were divided in to the following groups: I group (BMI = 18,5-24,9), II group (BMI = 25,0-29,9), III group (BMI = 30,0-34,9), IV group (BMI > 35). We determined uric acid level among women during postmenopausal period depending on their body mass index. The higher level of uric acid was found in patients with the maximal body mass index (BMI > 35). In the I group it was 277,52 ± 8,40; in the II group – 286,81 ± 7,79; in the III group – 291,81 ± 7,56; in the IV group – 327,17 ± 12,17. Incidence of hyperuricemia among women in the I group was 10,2%, in the II group – 15,9%; in the III group – 21,2%, in the IV group – 34,2%. We found an interdependence between an uric acid level and BMI in the examined women (r = 0,21, p < 0,05). We determined that the highest level of triglyceride (F = 18,62, p < 0,05), cholesterol (F = 3,64, p < 0,05), atherogenic coefficient (F = 22,64, p < 0,05), systolic (F = 10,5, p < 0,05) and diastolic pressure (F = 4,30, p < 0,05) was among women with hyperuricemia. It was an interdependence between an uric acid level and triglyceride (r = 0,26, p < 0,05), atherogenic coefficient (r = 0,24, p < 0,05) among women in postmenopausal period.

Keywords: hyperuricemia, uric acid, body mass index, women

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Authors: Kyugneun Lee, Ikjin Lee

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Parameter estimation with inverse problem often suffers from unfavorable conditions in the real world. Useless data and many input parameters make the problem complicated or insoluble. Data refinement and reformulation of the problem can solve that kind of difficulties. In this research, a method to solve the rank deficient inverse problem is suggested. A multi-physics system which has rank deficiency caused by response correlation is treated. Impeditive information is removed and the problem is reformulated to sequential estimations using Bayesian network (BN) and subset groups. At first, subset grouping of the responses is performed. Feature selection with singular value decomposition (SVD) is used for the grouping. Next, BN inference is used for sequential conditional estimation according to the group hierarchy. Directed acyclic graph (DAG) structure is organized to maximize the estimation ability. Variance ratio of response to noise is used to pairing the estimable parameters by each response.

Keywords: Bayesian network, feature selection, rank deficiency, statistical inverse analysis

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Authors: J. Vveinhardt, V. B. Fominiene, L. Jeseviciute-Ufartiene

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Relevance of Research: Qualitative research is still regarded as highly subjective and not sufficiently scientific in order to achieve objective research results. However, it is agreed that a qualitative study allows revealing the hidden motives of the research participants, creating new theories, and highlighting the field of problem. There is enough research done to reveal these qualitative research aspects. However, each research area has its own specificity, and sport is unique due to the image of its participants, who are understood as strong and invincible. Therefore, a sport participant might have personal issues to recognize himself as a victim in the context of bullying and harassment. Accordingly, researcher has a dilemma in general making to speak a victim in sport. Thus, ethical aspects of qualitative research become relevant. The plenty fields of sport make a problem determining the sample size of research. Thus, the corresponding problem of this research is which and why qualitative research strategies are the most suitable revealing the phenomenon of bullying and harassment in sport. Object of research is qualitative research strategy for bullying and harassment in sport. Purpose of the research is to analyze strategies of qualitative research selecting suitable one for bullying and harassment in sport. Methods of research were scientific research analyses of qualitative research application for bullying and harassment research. Research Results: Four mane strategies are applied in the qualitative research; inductive, deductive, retroductive, and abductive. Inductive and deductive strategies are commonly used researching bullying and harassment in sport. The inductive strategy is applied as quantitative research in order to reveal and describe the prevalence of bullying and harassment in sport. The deductive strategy is used through qualitative methods in order to explain the causes of bullying and harassment and to predict the actions of the participants of bullying and harassment in sport and the possible consequences of these actions. The most commonly used qualitative method for the research of bullying and harassment in sports is semi-structured interviews in speech and in written. However, these methods may restrict the openness of the participants in the study when recording on the dictator or collecting incomplete answers when the participant in the survey responds in writing because it is not possible to refine the answers. Qualitative researches are more prevalent in terms of technology-defined research data. For example, focus group research in a closed forum allows participants freely interact with each other because of the confidentiality of the selected participants in the study. The moderator can purposefully formulate and submit problem-solving questions to the participants. Hence, the application of intelligent technology through in-depth qualitative research can help discover new and specific information on bullying and harassment in sport. Acknowledgement: This research is funded by the European Social Fund according to the activity ‘Improvement of researchers’ qualification by implementing world-class R&D projects of Measure No. 09.3.3-LMT-K-712.

Keywords: bullying, focus group, harassment, narrative, sport, qualitative research

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Authors: Hung Ton

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The Vietnamese community in Toronto, Ontario, Canada, is a minority group with an estimated less than 1% of the population. They have been in Canada since the 1970s, therefore, many funding sources are considering them as a long-time residential group. However, their limitation of resources cannot give them equal opportunities to successfully gain support from many levels of government in Canada, compared to other long-time settled and large groups. In 2020 and 2021, they have zero financial support for addressing problem gambling in the Vietnamese community. In contrast, casinos never forget this community. The gambling industry has been targeting the Vietnamese community as one of their major clientele groups. There are always in-equal battles between low-budget educational workshops by this underserved community group and expensive variety music shows by casinos. In the very same target group, five single lines of free ads by a community project cannot get more attention than a full-page colorful poster by casinos. An outreach worker is running back and forth to talk to a group of 10 or 15 persons in an ESL or Tai Chi class held in a basement of an old community center while fifty thousand dollars variety music shows can attract five thousand audience in their luxury facilities. Five-dollar vouchers for those who attend the problem gambling awareness session are incomparable to two hundred dollar free tickets for people to attend the show in casinos and then exit the gambling area after the show ends. There is only one problem gambling counselor who speaks the Vietnamese language in the Ontario province and in Canada at large. However, there are 70 casinos in Ontario and more than 200 licensed gambling facilities in Canada. He has been lonely in all in-equal "battles" for the last almost 25 years. He exists, fighting over there with or without funding support for the program, he fights still.

Keywords: Canadian Vietnamese, gambling addiction, gambling treatment, community awareness

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Authors: Muhalim Muhalim

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Drawing on Lakoff’s theory of metaphor conceptualization, this article explores the conceptualization of language two writing (L2W) of ten students-teachers in Indonesia via metaphors. The ten postgraduate English language teaching students and at the same time (former) English teachers received seven days of intervention in teaching and learning L2. Using introspective log and focus group discussion, the results illuminate us that all participants are unanimous on perceiving L2W as process-oriented rather than product-oriented activity. Specifically, the metaphor conceptualizations exhibit three categories of process-oriented L2W: deliberate process, learning process, and problem-solving process. However, it has to be clarified from the outset that this categorization is not rigid because some of the properties of metaphors might belong to other categories. Results of the study and implications for English language teaching will be further discussed.

Keywords: metaphor conceptualisation, second language, learning writing, teaching writing

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Authors: Srushti Bhatt, M. B. Kiran

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Two-sided assembly line balancing problem is yet to be addressed simply to compete for the global market for manufacturers. The task assigned in an ordered sequence to get optimum performance of the system is known as assembly line balancing problem mainly classified as single and two sided. It is very challenging in manufacturing industries to balance two-sided assembly line, wherein the set of sequential workstations the task operations are performed in two sides of the line. The conflicting major objective in two-sided assembly line balancing problem is either to maximize /minimize the performance parameters. The present study emphases on combining different evolutionary algorithm; ant colony, Tabu search and petri net method; and compares their results of an algorithm for solving two-sided assembly line balancing problem. The concept of multi objective optimization of performance parameters is now a day adopted to make a decision involving more than one objective function to be simultaneously optimized. The optimum result can be expected among the selected methods using multi-objective optimization. The performance parameters considered in the present study are a number of workstation, slickness and smoothness index. The simulation of the assembly line balancing problem provides optimal results of classical and practical problems.

Keywords: Ant colony, petri net, tabu search, two sided ALBP

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Authors: Kostas Metaxiotis

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Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.

Keywords: evolutionary algorithms, portfolio optimization, skewness, stock selection

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Authors: Houda Abadlia, Nadia Smairi, Khaled Ghedira

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Multiobjective Particle Swarm Optimization (MOPSO) has shown an effective performance for solving test functions and real-world optimization problems. However, this method has a premature convergence problem, which may lead to lack of diversity. In order to improve its performance, this paper presents a hybrid approach which embedded the MOPSO into the island model and integrated a local search technique, Variable Neighborhood Search, to enhance the diversity into the swarm. Experiments on two series of test functions have shown the effectiveness of the proposed approach. A comparison with other evolutionary algorithms shows that the proposed approach presented a good performance in solving multiobjective optimization problems.

Keywords: particle swarm optimization, migration, variable neighborhood search, multiobjective optimization

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Authors: Halil Ibrahim Demir, Caner Erden, Abdullah Hulusi Kokcam, Mumtaz Ipek

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Process planning, scheduling, and due date assignment are three important manufacturing functions which are studied independently in literature. There are hundreds of works on IPPS and SWDDA problems but a few works on IPPSDDA problem. Integrating these three functions is very crucial due to the high relationship between them. Since the scheduling problem is in the NP-Hard problem class without any integration, an integrated problem is even harder to solve. This study focuses on the integration of these functions. Sum of weighted tardiness, earliness, and due date related costs are used as a penalty function. Random search and hybrid metaheuristics are used to solve the integrated problem. Marginal improvement in random search is very high in the early iterations and reduces enormously in later iterations. At that point directed search contribute to marginal improvement more than random search. In this study, random and genetic search methods are combined to find better solutions. Results show that overall performance becomes better as the integration level increases.

Keywords: process planning, genetic algorithm, hybrid search, random search, weighted due-date assignment, weighted scheduling

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Authors: Reza Mollapourasl, Majid Haghi

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In this study, we develop local meshfree methods known as radial basis function-generated finite difference (RBF-FD) method and Hermite finite difference (RBF-HFD) method to design stencil weights and spatial discretization for Helmholtz equation. The convergence and stability of schemes are investigated numerically in three dimensions with irregular shaped domain. These localized meshless methods incorporate the advantages of the RBF method, finite difference and Hermite finite difference methods to handle the ill-conditioning issue that often destroys the convergence rate of global RBF methods. Moreover, numerical illustrations show that the proposed localized RBF type methods are efficient and applicable for problems with complex geometries. The convergence and accuracy of both schemes are compared by solving a test problem.

Keywords: radial basis functions, Hermite finite difference, Helmholtz equation, stability

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Authors: F. Hamidi, N. Amiri, H. Mishmast Nehi

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The Bilevel Programming (BP) model has been presented for a decision making process that consists of two decision makers in a hierarchical structure. In fact, BP is a model for a static two person game (the leader player in the upper level and the follower player in the lower level) wherein each player tries to optimize his/her personal objective function under dependent constraints; this game is sequential and non-cooperative. The decision making variables are divided between the two players and one’s choice affects the other’s benefit and choices. In other words, BP consists of two nested optimization problems with two objective functions (upper and lower) where the constraint region of the upper level problem is implicitly determined by the lower level problem. In real cases, the coefficients of an optimization problem may not be precise, i.e. they may be interval. In this paper we develop an algorithm for solving interval bilevel linear fractional programming problems. That is to say, bilevel problems in which both objective functions are linear fractional, the coefficients are interval and the common constraint region is a polyhedron. From the original problem, the best and the worst bilevel linear fractional problems have been derived and then, using the extended Charnes and Cooper transformation, each fractional problem can be reduced to a linear problem. Then we can find the best and the worst optimal values of the leader objective function by two algorithms.

Keywords: best and worst optimal solutions, bilevel programming, fractional, interval coefficients

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Authors: Benedict Barnes, Anthony Y. Aidoo

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A Divergence Regularization Method (DRM) is used to regularize the ill-posed Helmholtz equation where the boundary deflection is inhomogeneous in a Hilbert space H. The DRM incorporates a positive integer scaler which homogenizes the inhomogeneous boundary deflection in Cauchy problem of the Helmholtz equation. This ensures the existence, as well as, uniqueness of solution for the equation. The DRM restores all the three conditions of well-posedness in the sense of Hadamard.

Keywords: divergence regularization method, Helmholtz equation, ill-posed inhomogeneous Cauchy boundary conditions

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Authors: Mohammad H. Ahmadi, Vahid Haghighatdoost

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Given a set of source locations for a group of friends, and a set of trip plans for each group member as a sequence of Categories-of-Interests (COIs) (e.g., restaurant), and finally a specific COI as a common destination that all group members will gather together, in Meeting Point Based on Trip Plans (MPTPs) queries our goal is to find a Point-of-Interest (POI) from different COIs, such that the aggregate travel distance for the group is minimized. In this work, we considered two cases for aggregate function as Sum and Max. For solving this query, we propose an efficient pruning technique for shrinking the search space. Our approach contains three steps. In the first step, it prunes the search space around the source locations. In the second step, it prunes the search space around the centroid of source locations. Finally, we compute the intersection of all pruned areas as the final refined search space. We prove that the POIs beyond the refined area cannot be part of optimal answer set. The paper also covers an extensive performance study of the proposed technique.

Keywords: meeting point, trip plans, road networks, spatial databases

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Authors: Ken Hampshire, Thomas Mazzuchi, Shahram Sarkani

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As a subset of metaheuristics, nature-inspired optimization algorithms such as particle swarm optimization (PSO) have shown promise both in solving intractable problems and in their extensibility to novel problem formulations due to their general approach requiring few assumptions. Unfortunately, single instantiations of algorithms require detailed tuning of parameters and cannot be proven to be best suited to a particular illustrative problem on account of the “no free lunch” (NFL) theorem. Using these algorithms in real-world problems requires exquisite knowledge of the many techniques and is not conducive to reconciling the various approaches to given classes of problems. This research aims to present a unified view of PSO-based approaches from the perspective of relevant systems engineering problems, with the express purpose of then eliciting the best solution for any problem formulation in an ensemble learning bucket of models approach. The central hypothesis of the research is that extending the PSO algorithms found in the literature to real-world optimization problems requires a general ensemble-based method for all problem formulations but a specific implementation and solution for any instance. The main results are a problem-based literature survey and a general method to find more globally optimal solutions for any systems engineering optimization problem.

Keywords: particle swarm optimization, nature-inspired optimization, metaheuristics, systems engineering, ensemble learning

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Authors: Nurwati Djaman, Suradi Tahmir, Nurdin Arsyad

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The major objective of this study was to implement and evaluate the use of the implementation of social responsibility with the approach of Indonesian Realistic Mathematics Education (PMRI) in teaching and learning mathematics on students’ engagement and learning. The research problems investigated in this research: 1) What were the effects of the implementation of social responsibility with PMRI approach to learning mathematics? 2) What were the effects of the approach to students’ engagement? An action research and grounded theory methodology were adopted for the study. This study used mixed methods to collect, describe, and interpret the data. The data were collected through focus group discussion, classroom observations, questionnaire, interview, and students’ work. The participants in this study consisted of 45 students. The study revealed that the approach has given students the opportunity to develop their understanding of concepts and procedures, problem-solving ability, and communication ability. Also, students’ involvement in the approach improved their engagement in learning mathematics in the three domains of cognitive engagement, effective engagement, and behavioral engagement. In particular, the data collection from the focus group, classroom observations, and interviews suggest that, during this study, the students became more active participants in the mathematics lessons.

Keywords: Indonesian Realistic Mathematics Education, PMRI, learning mathematics, social responsibility, students' engagement

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Authors: Yasin Tadayonrad

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading /unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is loading/unloading capacity in each source/ destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming

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Authors: Bezhan Ghvaberidze

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A multiple criteria optimization approach for the solution of the Fuzzy Vehicle Routing Problem (FVRP) is proposed. For the possibility environment the levels of movements between customers are calculated by the constructed simulation interactive algorithm. The first criterion of the bi-criteria optimization problem - minimization of the expectation of total fuzzy travel time on closed routes is constructed for the FVRP. A new, second criterion – maximization of feasibility of movement on the closed routes is constructed by the Choquet finite averaging operator. The FVRP is reduced to the bi-criteria partitioning problem for the so called “promising” routes which were selected from the all admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in the real-time computing. For the numerical solution of the bi-criteria partitioning problem the -constraint approach is used. An exact algorithm is implemented based on D. Knuth’s Dancing Links technique and the algorithm DLX. The Main objective was to present the new approach for FVRP, when there are some difficulties while moving on the roads. This approach is called FVRP for extreme conditions (FVRP-EC) on the roads. Also, the aim of this paper was to construct the solving model of the constructed FVRP. Results are illustrated on the numerical example where all Pareto-optimal solutions are found. Also, an approach for more complex model FVRP with time windows was developed. A numerical example is presented in which optimal routes are constructed for extreme conditions on the roads.

Keywords: combinatorial optimization, Fuzzy Vehicle routing problem, multiple objective programming, possibility theory

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Authors: Kamel Abd Elaziz Mohamed

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Introduction: Drug related problems (DRPs) are of major concern, affecting patients of both sex. They impose considerable economic burden on the society and the health-care systems. Aim of the work: The aim of this work was to identify and categorize drug-related problems in adult intensive care unit. Patients and methods: The study was a prospective, observational study as eighty six patients were included. They were consecutively admitted to ICU through the emergency room or transferred from the general ward due to DRPs. Parameters included in the study as length of stay in ICU, need for cardiovascular support or mechanical ventilation, dialysis, as well as APACHE II score were recorded. Results: Drug related problems represent 3.6% of the total ICU admission. The median (range) of APACHE II score for 86 patients included in the study was 17 (10-23), and length of ICU stay was 2.4 (1.5-4.2) days. In 45 patients (52%), DRP was drug over dose (group 1), while other DRP was present in the other 41 patients (48%, group 11). Patients in group 1 were older (39 years versus 32 years in group 11), with significant impaired renal function. The need of inotropic drugs and mechanical ventilation as well as the length of stay (LOS) in ICU was significantly higher in group 1. There were no significant difference in GCS between both groups, however APACHE II score was significantly higher in group 1. Only four patients (4.6%) were admitted by suicidal attempt as well as three patients (3.4%) due to trauma drug-related admissions, all were in (group 1). Nineteen percent of the patients had drug related problem due to hypoglycaemic medication followed by tranquilizer (15%). Adverse drug effect followed by failure to receive medication were the most causes of drug problem in (group11).The total mortality rate was 4.6%, all of them were eventually non preventable. Conclusion: The critically ill patients admitted due to drug related problems represented a small proportion (3.6%) of admissions to the ICU. Hypoglycaemic medication was one of the most common causes of admission by drug related problems.

Keywords: drug related problems, ICU, cost, safety

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Authors: Boumesbah Asma, Chergui Mohamed El-amine

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Since it has been shown that the multi-objective minimum spanning tree problem (MOST) is NP-hard even with two criteria, we propose in this study a hybrid NSGA-II algorithm with an exact mutation operator, which is only used with low probability, to find an approximation to the Pareto front of the problem. In a connected graph G, a spanning tree T of G being a connected and cycle-free graph, if k edges of G\T are added to T, we obtain a partial graph H of G inducing a reduced size multi-objective spanning tree problem compared to the initial one. With a weak probability for the mutation operator, an exact method for solving the reduced MOST problem considering the graph H is then used to give birth to several mutated solutions from a spanning tree T. Then, the selection operator of NSGA-II is activated to obtain the Pareto front approximation. Finally, an adaptation of the VNS metaheuristic is called for further improvements on this front. It allows finding good individuals to counterbalance the diversification and the intensification during the optimization search process. Experimental comparison studies with an exact method show promising results and indicate that the proposed algorithm is efficient.

Keywords: minimum spanning tree, multiple objective linear optimization, combinatorial optimization, non-sorting genetic algorithm, variable neighborhood search

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Authors: Luciana Abednego, Cecilia Nugraheni

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There are many approaches proposed for solving Sudoku puzzles. One of them is by modelling the puzzles as block world problems. There have been three model for Sudoku solvers based on this approach. Each model expresses Sudoku solver as a parameterized multi agent systems. In this work, we propose a new model which is an improvement over the existing models. This paper presents the development of a Sudoku solver that implements all the proposed models. Some experiments have been conducted to determine the performance of each model.

Keywords: Sudoku puzzle, Sudoku solver, block world problem, parameterized multi agent systems

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Authors: Maya Saade, Rafic Younes, Pascal Lafon

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This paper explores the transformative impact of smartphones on pedagogy and presents a smartphone application developed specifically for engineering problem-solving and educational purposes. The widespread availability and advanced capabilities of smartphones have revolutionized the way we interact with technology, including in education. The ubiquity of smartphones allows learners to access educational resources anytime and anywhere, promoting personalized and self-directed learning. The first part of this paper discusses the overall influence of smartphones on pedagogy, emphasizing their potential to improve learning experiences through mobile technology. In the context of engineering education, this paper focuses on the development of a dedicated smartphone application that serves as a powerful tool for both engineering problem-solving and education. The application features an intuitive and user-friendly interface, allowing engineering students and professionals to perform complex calculations and analyses on their smartphones. The smartphone application primarily focuses on beam calculations and serves as a comprehensive beam calculator tailored to engineering education. It caters to various engineering disciplines by offering interactive modules that allow students to learn key concepts through hands-on activities and simulations. With a primary emphasis on beam analysis, this application empowers users to perform calculations for statically determinate beams, statically indeterminate beams, and beam buckling phenomena. Furthermore, the app includes a comprehensive library of engineering formulas and reference materials, facilitating a deeper understanding and practical application of the fundamental principles in beam analysis. By offering a wide range of features specifically tailored for beam calculation, this application provides an invaluable tool for engineering students and professionals looking to enhance their understanding and proficiency in this crucial aspect of a structural engineer.

Keywords: mobile devices in education, solving engineering problems, smartphone application, engineering education

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Authors: S. R. Santhanam

Abstract:

A gifted child is one who gives evidence of creativity, good memory, rapid learning. In mathematics, a teacher often comes across some gifted children and they exhibit the following characteristics: unusual alertness, enjoying solving problems, getting bored on repetitions, self-taught, going beyond what teacher taught, ask probing questions, connecting unconnected concepts, vivid imagination, readiness for research work, perseverance of a topic. There are two main areas of research carried out on them: 1)identifying gifted children, 2) interacting and channelizing them. A lack of appropriate recognition will lead the gifted child demotivated. One of the main findings is if proper attention and nourishment are not given then it leads a gifted child to become depressed, underachieving, fail to reach their full potential and sometimes develop negative attitude towards school and study. After identifying them, a mathematics teacher has to develop them into a fall fledged achiever. The responsibility of the teacher is enormous. The teacher has to be resourceful and patient. But interacting with them one finds a lot of surprises and awesomeness. The elementary algebraic identities like (a+b)(a-b)=a²-b², expansion of like (a+b)²(a-b)² and others are taught to students, of age group 13-15 in India. An average child will be satisfied with a single proof and immediate application of these identities. But a gifted child expects more from the teacher and at one stage after a little training will surpass the teacher also. In this short paper, the author shares his experience regarding teaching algebraic identities to gifted children. The following problem was given to a set of 10 gifted children of the specified age group: If a natural number ‘n’ to expressed as the sum of the two squares, will 2n also be expressed as the sum of two squares? An investigation has been done on what multiples of n satisfying the criterion. The attempts of the gifted children were consolidated and conclusion was drawn. A second problem was given to them as: can two natural numbers be found such that the difference of their square is 3? After a successful solution, more situations were analysed. As a third question, the finding of the sign of an algebraic expression in three variables was analysed. As an example: if a,b,c are real and unequal what will be sign of a²+4b²+9c²-4ab-12bc-6ca? Apart from an expression as a perfect square what other methods can be employed to prove an algebraic expression as positive negative or non negative has been analysed. Expressions like 4x²+2y²+13y²-2xy-4yz-6zx were given, and the children were asked to find the sign of the expression for all real values of x,y and z. In all investigations, only basic algebraic identities were used. As a next probe, a divisibility problem was initiated. When a,b,c are natural numbers such that a+b+c is at least 6, and if a+b+c is divisible by 6 then will 6 divide a³+b³+c³. The gifted children solved it in two different ways.

Keywords: algebraic identities, gifted children, Indian scenario, research

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Authors: Dmitri Terzi

Abstract:

The article presents the results of an algorithmic study of a special optimization problem of the transport type (traveling salesman problem): 1) To solve the problem, a new natural algorithm has been developed based on the decomposition of the initial data into convex hulls, which has a number of advantages; it is applicable for a fairly large dimension, does not require a large amount of memory, and has fairly good performance. The relevance of the algorithm lies in the fact that, in practice, programs for problems with the number of traversal points of no more than twenty are widely used. For large-scale problems, the availability of algorithms and programs of this kind is difficult. The proposed algorithm is natural because the optimal solution found by the exact algorithm is not always feasible due to the presence of many other factors that may require some additional restrictions. 2) Another inverse problem solved here is to describe a class of traveling salesman problems that have a predetermined optimal solution. The constructed algorithm 2 allows us to characterize the structure of traveling salesman problems, as well as construct test problems to evaluate the effectiveness of algorithms and other purposes. 3) The appendix presents a software implementation of Algorithm 1 (in MATLAB), which can be used to solve practical problems, as well as in the educational process on operations research and optimization methods.

Keywords: traveling salesman problem, solution construction algorithm, convex hulls, optimality verification

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Authors: Taisir Eldos, Aws Kanan, Waleed Nazih, Ahmad Khatatbih

Abstract:

Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept.

Keywords: evolutionary algorithms, chemical reaction optimization, traveling salesman, board drilling

Procedia PDF Downloads 487