Search results for: firm objective

Authors: Álvaro Turriago-Hoyos

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Most research tends to see innovation as an explanatory factor in achieving high levels of competitiveness and productivity. More recent studies have begun to analyze the determinants of innovation in the services sector as opposed to the much-discussed industrial sector of a country’s economy. This research paper focuses on the services sector in Colombia, one of Latin America’s fastest growing and biggest economies. Over the past decade, much of Colombia’s economic expansion has relied on commodity exports (mainly oil and coffee) whilst the industrial sector has performed relatively poorly. Such developments highlight the potential of the innovative role played by the services sector of the Colombian economy and its future growth prospects. This research paper analyzes the relationship between inputs, which at the same time are internal sources of innovation (such as R&D activities), and external sources that are improved by technology acquisition. The outputs are basically the four kinds of innovation that the OECD Oslo Manual recognizes: product, process, marketing and organizational innovations. The instrument used to measure this input-output relationship is based on Knowledge Production Function approaches. We run Probit models in order to identify the existing relationships between the above inputs and outputs, but also to identify spill-overs derived from interactions of the components of the value chain of the services firms analyzed: customers, suppliers, competitors, and complementary firms. Data are obtained from the Colombian National Administrative Department of Statistics for the period 2008 to 2013 published in the II and III Colombian National Innovation Survey. A short summary of the results obtained lead to conclude that firm size and a firm’s level of technological development turn out to be important discriminating factors for the description of the innovative process at the firm level. The model’s outcomes show a positive impact on the probability of introducing any kind of innovation both on R&D and Technology Acquisition investment. Also, cooperation agreements with customers, research institutes, competitors, and the suppliers are significant. Belonging to a particular industrial group is an important determinant but only to product and organizational innovation. It is possible to establish that Health Services, Education, Computer, Wholesale trade, and Financial Intermediation are the ISIC sectors, which report the highest number of frequencies of the considered set of firms. Those five sectors of the sixteen considered, in all cases, explained more than half of the total of all kinds of innovations. Product Innovation, which is followed by Marketing Innovation, gets the highest results. Displaying the same set of firms distinguishing by size, and belonging to high and low tech services sector shows that the larger the firms the larger a number of innovations, but also that always high-tech firms show a better innovation performance.

Keywords: Colombia, determinants of innovation, innovation, services sector

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Authors: S. Adhirai, R. P. Mahapatra, Paramjit Singh

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Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.

Keywords: optimization, optimal value, objective function, optimization problems, meta-heuristic optimization algorithms, Whale Optimization Algorithm, implementation, MATLAB

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Authors: Mohammed Elsayed Lotfy Elsayed Abouzeid, Tomonobu Senjyu

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A novel multi-objective park and ride control approach is presented in this research. Park and ride will encourage the owners of the vehicles to leave their cars in the nearest points (on the edges of the crowded cities) and use public transportation facilities (train, bus, metro, or mon-rail) to reach their work inside the crowded city. The proposed control scheme is used to design electric vehicle charging stations (EVCS) to charge 1000 electric vehicles (EV) during their owners' work time. Cairo, Egypt is used as a case study. Photovoltaic (PV) and battery energy storage system (BESS) are used to meet the EVCS demand. Two multi-objective optimization techniques (MOGA and epsilon-MOGA) are utilized to get the optimal sizes of PV and BESS so as to meet the load demand and minimize the total life cycle cost. Detailed analysis and comparison are held to investigate the performance of the proposed control scheme using MATLAB.

Keywords: Battery Energy Storage System, Electric Vehicle, Park and Ride, Photovoltaic, Multi-objective

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Authors: Majdi Anwar Quttainah, William Paczkowski, Ali Muhammad

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Determining the value of a privately held firms confound those in academia as well as practitioners in the fields of appraisal, forensic accounting, and law. Divergent parties to the transfer look to apply the valuation technique to serve their own best interests. This paper seeks to explore how agency theory induces owners to choose the form of their businesses at inception and how this choice will affect the appraisers’ valuation of the firm at the transfer of ownership.

Keywords: organizational form, agency theory, value

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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: Ghorbanali Mohammadi

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New approaches to sequencing mixed-model manufacturing systems are present. These approaches have attracted considerable attention due to their potential to deal with difficult optimization problems. This paper presents Multi-Objective Simulated Annealing Algorithms (MOSAA) approaches to the Just-In-Time (JIT) sequencing problem where workload-smoothing (WL) and the number of set-ups (St) are to be optimized simultaneously. Mixed-model assembly lines are types of production lines where varieties of product models similar in product characteristics are assembled. Moreover, this type of problem is NP-hard. Two annealing methods are proposed to solve the multi-objective problem and find an efficient frontier of all design configurations. The performances of the two methods are tested on several problems from the literature. Experimentation demonstrates the relative desirable performance of the presented methodology.

Keywords: scheduling, just-in-time, mixed-model assembly line, sequencing, simulated annealing

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Authors: Geuna Kim, Sanghyun Kim

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This study investigates various factors that may influence the ISM process, including the organization’s internal needs and external pressure, and examines the role of regulatory pressure in ISM development and performance. The 105 sets of data collected in a survey were tested against the research model using SEM. The results indicate that NP and TP had positive effects on the ISM process, except for perceived benefits. Regulatory pressure had a positive effect on the relationship between ISM awareness and ISM development and performance.

Keywords: information security management, need pull, technology push, regulatory pressure

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Authors: Tunjo Perić, Franjo Bratić

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In this paper the goal programming methodology for solving multiple objective problem of the technological variants and production plan optimization has been applied. The optimization criteria are determined and the multiple objective linear programming model for solving a problem of the technological variants and production plan optimization is formed and solved. Then the obtained results are analysed. The obtained results point out to the possibility of efficient application of the goal programming methodology in solving the problem of the technological variants and production plan optimization. The paper points out on the advantages of the application of the goal programming methodolohy compare to the Surrogat Worth Trade-off method in solving this problem.

Keywords: goal programming, multi objective programming, production plan, SWT method, technological variants

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Authors: Arash Rahmani, Ahmad Ghanbari, Abbas Baghernezhad, Babak Safaei

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In the design of parallel manipulators, usually mean value of a dexterity measure over the workspace volume is considered as the objective function to be used in optimization algorithms. The mentioned indexes in a hybrid parallel manipulator (HPM) are quite complicated to solve thanks to infinite solutions for every point within the workspace of the redundant manipulators. In this paper, spatial isotropic design axioms are extended as a well-known method for optimum design of manipulators. An upper limit for the isotropy measure of HPM is calculated and instead of computing and minimizing isotropy measure, minimizing the obtained limit is considered. To this end, two different objective functions are suggested which are obtained from objective functions of comprising modules. Finally, by using genetic algorithm (GA), the best geometric parameters for a specific hybrid parallel robot which is composed of two modified Gough-Stewart platforms (MGSP) are achieved.

Keywords: hybrid manipulator, spatial isotropy, genetic algorithm, optimum design

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Authors: M. Şimşek

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Additive manufacturing (AM) or generally known as three dimensional (3D) printing provides great opportunities for both civilian and military applications by which 3D has become the biggest nominee of breakthrough of 21th century. When properly used, it has a wide spectrum of applications that make production easier and more profitable. Considering the advantages of AM, every firm has an intention of catching up with this new trend. As well as reducing costs and thus increasing benefits, 3D printing provides opportunities for national armies by reducing maintenance and repair time and increasing operational readiness.

Keywords: additive manufacturing, operational cost, operational readiness, supply chain, three dimensional printing

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Authors: Anvar Atayev, Karl Steinborn, Aleksander Lovric, Saif Al-Ibadi, Jorg Fliege

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In this paper, we present results obtained from optimising the aerodynamic performance of aerostructures in external ow. The optimisation method used was developed to efficiently handle multi-variable problems with numerous black-box objective functions and constraints. To demonstrate these capabilities, a series of CFD problems were considered; (1) a two-dimensional NACA aerofoil with three variables, (2) a two-dimensional morphing aerofoil with 17 variables, and (3) a three-dimensional morphing aeroplane tail with 33 variables. The objective functions considered were related to combinations of the mean aerodynamic coefficients, as well as their relative variations/oscillations. It was observed that for each CFD problem, an improved objective value was found. Notably, the scale-up in variables for the latter problems did not greatly hinder optimisation performance. This makes the method promising for scaled-up CFD problems, which require considerable computational resources.

Keywords: computational fluid dynamics, optimisation algorithms, aerodynamic design, engineering design

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Authors: E. T. L. Cöuras Ford, V. A. C. Vale, J. U. L. Mendes

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Two of the objective principal in the study of the aerodynamics of vehicles are the safety and the acting. Those objectives can be reached through the development of devices modify the drainage of air about of the vehicle and also through alterations in the way of the external surfaces. The front lowest profile of the vehicle, for instance, has great influence on the coefficient of aerodynamic penetration (Cx) and later on great part of the pressure distribution along the surface of the vehicle. The objective of this work was of analyzing the aerodynamic behavior that it happens on some types the trucks of vehicles, based on experimentation in aerodynamic tunnel, seeking to determine the aerodynamic efficiency of each one of them.

Keywords: aerodynamic, vehicles, wind tunnel, safety, acting

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Authors: Abdous Noureddine

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The problem of funding in Algeria emerged as a problem you need to study after many Algerians researchers pointed out that the faltering Algerian public economic institution due to the imbalance in the financial structures and lower steering and marketing efficiency, as well as a result of severe expansion of borrowing because of inadequate own resources, and the consequent inability This institution to repay loans and interest payments, in addition to increasing reliance on overdraft so used to finance fixed assets, no doubt that this deterioration requires research and study of the causes and aspects of treatment, which addresses the current study, aside from it.

Keywords: financial structure, financial capital, equity, debt, firm’s value, return, leverage

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Authors: Dale Dzemydiene, Aurelija Burinskiene, Arunas Miliauskas, Kristina Ciziuniene

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Data flow and the purpose of reporting the data are different and dependent on business needs. Different parameters are reported and transferred regularly during freight delivery. This business practices form the dataset constructed for each time point and contain all required information for freight moving decisions. As a significant amount of these data is used for various purposes, an integrating methodological approach must be developed to respond to the indicated problem. The proposed methodology contains several steps: (1) collecting context data sets and data validation; (2) multi-objective analysis for optimizing freight transfer services. For data validation, the study involves Grubbs outliers analysis, particularly for data cleaning and the identification of statistical significance of data reporting event cases. The Grubbs test is often used as it measures one external value at a time exceeding the boundaries of standard normal distribution. In the study area, the test was not widely applied by authors, except when the Grubbs test for outlier detection was used to identify outsiders in fuel consumption data. In the study, the authors applied the method with a confidence level of 99%. For the multi-objective analysis, the authors would like to select the forms of construction of the genetic algorithms, which have more possibilities to extract the best solution. For freight delivery management, the schemas of genetic algorithms' structure are used as a more effective technique. Due to that, the adaptable genetic algorithm is applied for the description of choosing process of the effective transportation corridor. In this study, the multi-objective genetic algorithm methods are used to optimize the data evaluation and select the appropriate transport corridor. The authors suggest a methodology for the multi-objective analysis, which evaluates collected context data sets and uses this evaluation to determine a delivery corridor for freight transfer service in the multi-modal transportation network. In the multi-objective analysis, authors include safety components, the number of accidents a year, and freight delivery time in the multi-modal transportation network. The proposed methodology has practical value in the management of multi-modal transportation processes.

Keywords: multi-objective, analysis, data flow, freight delivery, methodology

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Authors: Mandeep Kaur, Fatehgarh Sahib

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The purpose of economic load dispatch is to allocate the required load demand between the available generation units such that the cost of operation is minimized. It is an optimization problem to find the most economical schedule of the generating units while satisfying load demand and operational constraints. The multiobjective optimization problem in which the engineer’s goal is to maximize or minimize not a single objective function but several objective functions simultaneously. The purpose of multiobjective problems in the mathematical programming framework is to optimize the different objective functions. Many approaches and methods have been proposed in recent years to solve multiobjective optimization problems. Weighting method has been applied to convert multiobjective optimization problems into scalar optimization. MATLAB 7.10 has been used to write the code for the complete algorithm with the help of genetic algorithm (GA). The validity of the proposed method has been demonstrated on a three-unit power system.

Keywords: economic load dispatch, genetic algorithm, generating units, multiobjective optimization, weighting method

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Authors: Charles Amoatey, Ebenezer Kumah

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Purpose: The purpose of this paper is to assess the effects of implementation of Distributor Management Solution (DMS) on supply chain performance in the Fast Moving Consumer Goods (FMCG) industry in Ghana. Methodology: A purposive sampling approach was used in selecting the respondents for the study. Data was collected from senior management and field supervisors from sales, distribution and customer service units of the case study firm and its channel members. This study made use of systematic literature review and results of survey data analysis to assess how information system has been used to improve supply chain performance. Findings: Results from the study showed that the critical effect factors from implementation of a DMS include (1) Obtain prompt and reliable feedback from the market; (2) Building the capacity and skills levels of employees as well as 3rd Party Agents; (3) Motivated top management to invest in MIS; and (4) Performance improvement in sales route management. The most critical challenges to an effective and sustainable MIS implementation are lack of enough trained IT employees and high barriers to cultural change especially with distributors. The paper recommends consistent investment in IS infrastructure and development of IT skills. Research limitations/implications: This study contributes to the literature by exploring the effects of distribution management solution implementation and supply chain performance in a developing country context. Considering the fact that this study is based on data from only one case study firm and its channel members, generalization of the results should be treated with caution. Practical implications: The findings have confirmed the benefits of implementing a Management Information System. The result should encourage channel members to allocate adequate resources for building MIS capacity to enhance their supply chain performance. Originality/Value: In this paper, the relationship between DMS/MIS implementation and improvement in supply chain performance, in the Ghanaian context, has been established.

Keywords: distributor management solution, fast-moving consumer goods, supply chain management, information systems, Ghana

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

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Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: evolutionary computation, feature selection, classification, clustering

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Authors: Chen Guo, Heng Tang, Ben Niu

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Clustering splits objects into different groups based on similarity, making the objects have higher similarity in the same group and lower similarity in different groups. Thus, clustering can be treated as an optimization problem to maximize the intra-cluster similarity or inter-cluster dissimilarity. In real-world applications, the datasets often have some complex characteristics: sparse, overlap, high dimensionality, etc. When facing these datasets, simultaneously optimizing two or more objectives can obtain better clustering results than optimizing one objective. However, except for the objectives weighting methods, traditional clustering approaches have difficulty in solving multi-objective data clustering problems. Due to this, evolutionary multi-objective optimization algorithms are investigated by researchers to optimize multiple clustering objectives. In this paper, the Data Clustering algorithm based on Multi-objective Periodic Bacterial Foraging Optimization with two Learning Archives (DC-MPBFOLA) is proposed. Specifically, first, to reduce the high computing complexity of the original BFO, periodic BFO is employed as the basic algorithmic framework. Then transfer the periodic BFO into a multi-objective type. Second, two learning strategies are proposed based on the two learning archives to guide the bacterial swarm to move in a better direction. On the one hand, the global best is selected from the global learning archive according to the convergence index and diversity index. On the other hand, the personal best is selected from the personal learning archive according to the sum of weighted objectives. According to the aforementioned learning strategies, a chemotaxis operation is designed. Third, an elite learning strategy is designed to provide fresh power to the objects in two learning archives. When the objects in these two archives do not change for two consecutive times, randomly initializing one dimension of objects can prevent the proposed algorithm from falling into local optima. Fourth, to validate the performance of the proposed algorithm, DC-MPBFOLA is compared with four state-of-art evolutionary multi-objective optimization algorithms and one classical clustering algorithm on evaluation indexes of datasets. To further verify the effectiveness and feasibility of designed strategies in DC-MPBFOLA, variants of DC-MPBFOLA are also proposed. Experimental results demonstrate that DC-MPBFOLA outperforms its competitors regarding all evaluation indexes and clustering partitions. These results also indicate that the designed strategies positively influence the performance improvement of the original BFO.

Keywords: data clustering, multi-objective optimization, bacterial foraging optimization, learning archives

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Authors: Freddy Munzhelele

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Setting: the empirical research has shown that the life cycle theory has an impact on the firms’ financing decisions, particularly the dividend pay-outs. Accordingly, the life cycle theory posits that as a firm matures, it gets to a level and capacity where it distributes more cash as dividends. On the other hand, the young firms prioritise investment opportunities sets and their financing; thus, they pay little or no dividends. The research on firms’ financing decisions also demonstrated, among others, the adoption of trade-off and pecking order theories on the dynamics of firms capital structure. The trade-off theory talks to firms holding a favourable position regarding debt structures particularly as to the cost and benefits thereof; and pecking order is concerned with firms preferring a hierarchical order as to choosing financing sources. The case of life cycle hypothesis explaining the financial managers’ decisions as regards the firms’ capital structure dynamics appears to be an interesting link, yet this link has been neglected in corporate finance research. If this link is to be explored as an empirical research, the financial decision-making alternatives will be enhanced immensely, since no conclusive evidence has been found yet as to the dynamics of capital structure. Aim: the aim of this study is to examine the impact of life cycle theory on the capital structure dynamics trade-off and pecking order theories of firms listed in retail, industrial and mining sectors of the JSE. These sectors are among the key contributors to the GDP in the South African economy. Design and methodology: following the postpositivist research paradigm, the study is quantitative in nature and utilises secondary data obtainable from the financial statements of sampled firm for the period 2010 – 2022. The firms’ financial statements will be extracted from the IRESS database. Since the data will be in panel form, a combination of the static and dynamic panel data estimators will used to analyse data. The overall data analyses will be done using STATA program. Value add: this study directly investigates the link between the life cycle theory and the dynamics of capital structure decisions, particularly the trade-off and pecking order theories.

Keywords: life cycle theory, trade-off theory, pecking order theory, capital structure, JSE listed firms

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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: Antonin Ponsich, Eric Alfredo Rincon Garcia, Roman Anselmo Mora Gutierrez, Miguel Angel Gutierrez Andrade, Sergio Gerardo De Los Cobos Silva, Pedro Lara Velzquez

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The electoral zone design problem consists in redrawing the boundaries of legislative districts for electoral purposes in such a way that federal or state requirements are fulfilled. In Mexico, this process has been historically carried out by the National Electoral Institute (INE), by optimizing an integer nonlinear programming model, in which population equality and compactness of the designed districts are considered as two conflicting objective functions, while contiguity is included as a hard constraint. The solution technique used by the INE is a Simulated Annealing (SA) based algorithm, which handles the multi-objective nature of the problem through an aggregation function. The present work represents the first intent to apply a classical Multi-Objective Evolutionary Algorithm (MOEA), the second version of the Non-dominated Sorting Genetic Algorithm (NSGA-II), to this hard combinatorial problem. First results show that, when compared with the SA algorithm, the NSGA-II obtains promising results. The MOEA manages to produce well-distributed solutions over a wide-spread front, even though some convergence troubles for some instances constitute an issue, which should be corrected in future adaptations of MOEAs to the redistricting problem.

Keywords: multi-objective optimization, NSGA-II, redistricting, zone design problem

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Authors: Nida Iftikhar, Jamaluddin Thaheem, Bilal Iftikhar

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In the construction industry, adequate and effective decision-making can mean the difference between success and failure. Bidding is the most important element of the construction business since it is a mean by which contractors obtain work. This is probably the only option for any contractor firm to sustain in the market and achieve its objective of earning the profits by winning tenders. The capability to select most appropriate ventures not only defines the success and wellbeing of contractor firms but also their survival and sustainability in the industry. The construction practitioners are usually on their own when it comes to deciding on bidding for a project or not. Usually, experience-based solutions are offered where a lot of subjectivity is involved. This research has been opted considering the local construction industry of Pakistan in order to examine the critical success factors from contractors’ perspective while making bidding decisions, listing and evaluating critical factors in order of their importance, categorization of these factors into decision support & decision oppose groups and to develop a framework to help contractors in the decision-making process. Literature review, questionnaires, and structured interviews are used for identification and quantification of factors affecting bid/no bid decision-making. Statistical methods of ranking analysis and analytical hierarchy process of multi-criteria decision-making method are used for analysis. It is found that profitability, need for work and financial health of client are the most decisive factors in bid/no bid decision-making while project size, project type, fulfilling the tender conditions imposed by the client and relationship, identity & reputation of the client are least impact factors in bid/no bid decision-making. Further, to verify the developed framework, case studies have been conducted to evaluate the bid/no bid decision-making in building procurement. This is the first of its nature study in the context of the local construction industry and recommends using a holistic decision-making framework for such business-critical deliberations.

Keywords: bidding, bid decision-making, construction procurement, contractor

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: Kiyohiro Yamazaki

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The purpose of this paper is to examine the hypothesis explaining the mechanism in the case, where the product is deleted or reduced the fundamental function of the product through the product concept changes in the digital camera industry. This paper points out not owning the fundamental technology might cause the change of the product concept. Casio could create new competitive factor so that this paper discusses a possibility of the mechanism of changing the product concept.

Keywords: firm without fundamental technology, product development, product concept, digital camera industry, Casio

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Authors: Geoffrey Sinha

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This paper is primarily addressed to teachers who stand on the threshold of bringing technology and new media into their classrooms. Technology and new media, such as smart phones and tablets have changed the face of communication in general and of language teaching more specifically. New media has widespread appeal among young people in particular, so it is in the teacher’s best interests to bring new media into their lessons. It is the author’s firm belief that technology will never replace the teacher, but it is without question that the twenty-first century teacher must employ technology and new media in some form, or run the risk of failure. The level that one chooses to incorporate new media within their class is entirely in their hands.

Keywords: new media, social media, technology, education, language learning

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Authors: S. Abdourraziq, M. A. Abdourraziq

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One of the most famous and important applications of solar energy systems is water pumping. It is often used for irrigation or to supply water in countryside or private firm. However, the cost and the efficiency are still a concern, especially with a continued variation of solar radiation and temperature throughout the day. Then, the improvement of the efficiency of the system components is one of the different solutions to reducing the cost. In this paper, we will present a detailed definition of each element of a PV pumping system, and we will present the different MPPT algorithm used in the literature. Our system consists of a PV panel, a boost converter, a motor-pump set, and a storage tank.

Keywords: PV cell, converter, MPPT, MPP, PV pumping system

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Authors: Felipe Azocar Simonet, Luis Acosta Espejo

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In this article, we will try to find an efficient boundary approximation for the bi-objective location problem with coherent coverage for two levels of hierarchy (CCLP). We present the mathematical formulation of the model used. Supported efficient solutions and unsupported efficient solutions are obtained by solving the bi-objective combinatorial problem through the weights method using a Lagrangean heuristic. Subsequently, the results are validated through the DEA analysis with the GEM index (Global efficiency measurement).

Keywords: coherent covering location problem, efficient frontier, lagragian relaxation, data envelopment analysis

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Authors: Jarrod Haar, David Brougham

Abstract:

The present study explores the links between supporting employee well-being and the potential benefits to employee performance. We focus on employee innovative work behaviors (IWBs), which have three stages: (1) development, (2) adoption, and (3) implementation of new ideas and work methods. We explore the role of organizational support focusing on employee well-being via High-Performance Work Systems (HPWS). HPWS are HR practices that are designed to enhance employees’ skills, commitment, and ultimately, productivity. HPWS influence employee performance through building their skills, knowledge, and abilities and there is meta-analytic support for firm-level HPWS influencing firm performance, but less attention towards employee outcomes, especially innovation. We explore HPWS-wellbeing being offered (e.g., EAPs, well-being App, etc.) to capture organizational commitment to employee well-being. Under social exchange theory, workers should reciprocate their firm's offering of HPWS-wellbeing with greater efforts towards IWBs. Further, we explore playful work design as a mediator, which represents employees proactively creating work conditions that foster enjoyment/challenge but don’t require any design change to the job itself. We suggest HPWS-wellbeing can encourage employees to become more playful, and ultimately more innovative. Finally, beyond direct effects, we examine whether these relations are similar by gender and ultimately test a moderated mediation model. Using N=1135 New Zealand employees, we established measures with confirmatory factor analysis (CFA), and all measures had good psychometric properties (α>.80). We controlled for age, tenure, education, and hours worked and analyzed data using the PROCESS macro (version 4.2) specifically model 8 (moderated mediation). We analyzed overall IWB, and then again across the three stages. Overall, we find HPWS-wellbeing is significantly related to overall IWBs and the three stages (development, adoption, and implementation) individually. Similarly, HPWS-wellbeing shapes playful work design and playful work design predicts overall IWBs and the three stages individually. It only partially mediates the effects of HPWS-wellbeing, which retains a significant indirect effect. Moderation effects are supported, with males reporting a more significant effect from HPWS-wellbeing on playful work design but not IWB (or any of the three stages) than females. Females report higher playful work design when HPWS-wellbeing is low, but the effects are reversed when HPWS-wellbeing is high (males higher). Thus, males respond stronger under social exchange theory from HPWS-wellbeing, at least towards expressing playful work design. Finally, evidence of moderated mediation effects is found on overall IWBs and the three stages. Males report a significant indirect effect from HPWS-wellbeing on IWB (through playful work design), while female employees report no significant indirect effect. The benefits of playful work design fully account for their IWBs. The models account for small amounts of variance towards playful work design (12%) but larger for IWBs (26%). The study highlights a gap in the literature on HPWS-wellbeing and provides empirical evidence of their importance towards worker innovation. Further, gendered effects suggest these benefits might not be equal. The findings provide useful insights for organizations around how providing HR practices that support employee well-being are important, although how they work for different genders needs further exploration.

Keywords: human resource practices, wellbeing, innovation, playful work design

Procedia PDF Downloads 71

Authors: Saif Ullah, Guan Zailin, Xu Xianhao, He Zongdong, Wang Baoxi

Abstract:

Assembly line balancing problem is aimed to divide the tasks among the stations in assembly lines and optimize some objectives. In assembly lines the workload on stations is different from each other due to different tasks times and the difference in workloads between stations can cause blockage or starvation in some stations in assembly lines. Buffers are used to store the semi-finished parts between the stations and can help to smooth the assembly production. The assembly line balancing and buffer sizing problem can affect the throughput of the assembly lines. Assembly line balancing and buffer sizing problems have been studied separately in literature and due to their collective contribution in throughput rate of assembly lines, balancing and buffer sizing problem are desired to study simultaneously and therefore they are considered concurrently in current research. Current research is aimed to maximize throughput, minimize total size of buffers in assembly line and minimize workload variations in assembly line simultaneously. A multi objective optimization objective is designed which can give better Pareto solutions from the Pareto front and a simple example problem is solved for assembly line balancing and buffer sizing simultaneously. Current research is significant for assembly line balancing research and it can be significant to introduce optimization approaches which can optimize current multi objective problem in future.

Keywords: assembly line balancing, buffer sizing, Pareto solutions

Procedia PDF Downloads 480

Authors: Jilly John

Abstract:

The paper reports one of the study conducted to explore the dimensions of child rearing practice and effects of power difference among parents on child rearing practices adopted in the families. The first objective investigated dimensions of child rearing practices (a) overprotection (b) disciplinarian, (c) esteem building, (d) normal, (e) harsh (f) ridicule, and (g) rejection. The second objective investigated difference among father and mother on child rearing practices. The results of the study revealed that dimensions of child rearing practices are crucial variables which resulted in form of major deviations in distribution of parents in the seven dimensions. Analysis of objective two revealed that harsh and ridicule dimensions of child rearing practices are significantly different among father and mother. The dimensions are also different when the parents are employed and according to the type of families. Thus the results of the study present the possibility of changed child rearing practices among Indian families in relation to prevalent sociodemographic changes and indicate the necessity to re-examine culture-based explanations on child rearing practices.

Keywords: child rearing practices, dimensions of child rearing, difference among parents, Indian families

Procedia PDF Downloads 389