Competency‐based IT personnel selection using a hybrid SWARA and ARAS‐G methodology

In the knowledge economy, human capital is a key factor in any organization to achieve a sustainable competitive advantage. Thus, selection of competent personnel is the most important function of human resource managers. However, because of a wide range of criteria and organizational factors that affect the process, personnel selection is often regarded as a complex problem that can be answered through multicriteria decision‐making (MCDM) procedures. Despite the great importance of determining a comprehensive set of criteria, it has not gained enough attention in the literature. This study presents a competency framework with five criteria for choosing the best information technology (IT) expert from five alternatives. The stepwise weight assessment ratio analysis (SWARA) and grey additive ratio assessment (ARAS‐G) methods are also used to derive the criteria weights and provide the final alternative, respectively. The results reveal that subject competency is the major criteria in IT personnel selection.     

A hybrid genetic heuristic for scheduling parallel batch processing machines with arbitrary job sizes

This paper investigates the scheduling problem of parallel identical batch processing machines in which each machine can process a group of jobs simultaneously as a batch. Each job is characterized by its size and processing time. The processing time of a batch is given by the longest processing time among all jobs in the batch. Based on developing heuristic approaches, we proposed a hybrid genetic heuristic (HGH) to minimize makespan objective. To verify the performance of our algorithm, comparisons are made through using a simulated annealing (SA) approach addressed in the literature as a comparator algorithm. Computational experiments reveal that affording the knowledge of problem through using heuristic procedures, gives HGH the ability of finding optimal or near optimal solutions in a reasonable time.     

Manufacturing cell design using simulated annealing: An industrial application

In this paper, we give a brief summary of simulated annealing (SA) procedures used to solve combinatorial optimization problems. We then present the manufacturing cell design problem which consists of designing cells of limited size in order to minimize inter-cell traffic. We show how to use a SA approach to obtain a good, if not optimum, solution to this problem. Finally, we apply this approach to an industrial problem and compare the results to the ones obtained using the so-called twofold heuristic algorithm.     

基于区间二型模糊决策粗糙集的三支决策方法

考虑到区间二型模糊数在描述高度不确定性信息方面的优势,将区间二型模糊数拓展到决策粗糙集中,提出两种区间二型模糊三支决策方法.在没有类标签的区间二型模糊信息系统中,解释损失函数与确定条件概率是需要解决的两个关键问题.首先,根据区间二型模糊数的性质,将其引入决策粗糙集中,为损失函数提供一种新的解释.其次,基于贝叶斯决策过程...     

A simulated annealing heuristic for the truck and trailer routing problem with time windows

European firms have been using a combination of trucks and trailers in the delivery/collection of food products for years. Thus, some previous studies had been devoted to improving the efficiency of the resulting truck and trailer routing problem (TTRP). Since time window constraints are present in many real-world routing applications, in this study, we introduce the truck and trailer routing problem with time windows (TTRPTW) to bring the TTRP model closer to the reality. A simulated annealing (SA) heuristic is proposed for solving the TTRPTW. Two computational experiments are conducted to test the performance of the proposed SA heuristic. The results indicate that the proposed SA heuristic is capable of consistently producing quality solutions to the TTRPTW within a reasonable time.     

Knowledge transfer in IT offshoring relationships: the roles of social capital,efficacy and outcome expectations

Information technology (IT) development in global organisations relies heavily on the transfer of tacit and complex knowledge from onshore units to offshore subsidiaries. A central concern of such organisations is the development of social capital, which is known to facilitate the smooth transfer of knowledge. However, only a few studies in IS research have explicitly examined the role of social capital for knowledge transfer in an IT offshoring context. In this paper, we argue that such knowledge transfer mechanisms can be understood better by considering social capital in concert with knowledge senders' efficacy and outcome expectations, two of the potentially key motivational drivers of knowledge transfer. We develop our arguments through a qualitative case study of a large German multinational company. German IT developers in this firm provided in‐depth accounts of their experience with offshore colleagues in an Indian captive subsidiary unit. Drawing on our analysis, we develop a model that depicts the influence of social capital, efficacy and outcome expectations on onshore IT developers' ability and willingness to transfer knowledge to offshore colleagues. Through the model, we also explain how social capital, efficacy and outcome expectations are interrelated and generate three interlocked, self‐reinforcing circles of knowledge transfer success in IT offshoring relationships.     

QoRank: A query‐dependent ranking model using LSE‐based weighted multiple hyperplanes aggregation for information retrieval

Ranking is a core problem for information retrieval since the performance of the search system is directly impacted by the accuracy of ranking results. Ranking model construction has been the focus of both the fields of information retrieval and machine learning, and learning to rank in particular has attracted much interest. Many ranking models have been proposed, for example, RankSVM is a state‐of‐the‐art method for learning to rank and has been empirically demonstrated to be effective. However, most of the proposed methods do not consider about the significant differences between queries, only resort to a single function in ranking. In this paper, we present a novel ranking model named QoRank, which performs the learning task dependent on queries. We also propose a LSE (least‐squares estimation) ‐based weighted method to aggregate the ranking lists produced by base decision functions as the final ranking. Comparison of QoRank with other ranking techniques is conducted, and several evaluation criteria are employed to evaluate its performance. Experimental results on the LETOR OHSUMED data set show that QoRank strikes a good balance of accuracy and complexity, and outperforms the baseline methods. © 2010 Wiley Periodicals, Inc.     

Simulated annealing heuristics for the dynamic facility layout problem

In today's economy, manufacturing plants must be able to operate efficiently and respond quickly to changes in product mix and demand. Therefore, this paper considers the problem of arranging and rearranging (when there are changes between the flows of materials between departments) manufacturing facilities such that the sum of the material handling and rearrangement costs is minimized. This problem is known as the dynamic facility layout problem (DFLP). In this paper, two simulated annealing (SA) heuristics are developed for the DFLP. The first SA heuristic (SA I) is a direct adaptation of SA to the DFLP. The second SA heuristic (SA II) is the same as SA I with a look-ahead/look-back strategy added. To test the performance of the heuristics, a data set taken from the literature is used in the analysis. The results obtained show that the proposed heuristics are very effective for the dynamic facility layout problem.     

Project risk evaluation using a fuzzy analytic hierarchy process: An application to information technology projects

Projects are critical to the realization of performing organization's strategies. Each project contains some degree of risk and it is required to be aware of these risks and to develop the necessary responses to get the desired level of project success. Because projects' risks are multidimensional, they must be evaluated by using multi‐attribute decision‐making methods. The aim of this article is to provide an analytic tool to evaluate the project risks under incomplete and vague information. The fuzzy analytic hierarchy process (AHP) as a suitable and practical way of evaluating project risks based on the heuristic knowledge of experts is used to evaluate the riskiness of an information technology (IT) project of a Turkish firm. The means of the triangular fuzzy numbers produced by the IT experts for each comparison are successfully used in the pairwise comparison matrices. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 559–584, 2006.     

Assembly line balancing using genetic algorithms

Assembly Line Balancing (ALB) is one of the important problems of production/operations management area. As small improvements in the performance of the system can lead to significant monetary consequences, it is of utmost importance to develop practical solution procedures that yield high-quality design decisions with minimal computational requirements. Due to the NP-hard nature of the ALB problem, heuristics are generally used to solve real life problems. In this paper, we propose an efficient heuristic to solve the deterministic and single-model ALB problem. The proposed heuristic is a Genetic Algorithm (GA) with a special chromosome structure that is partitioned dynamically through the evolution process. Elitism is also implemented in the model by using some concepts of Simulated Annealing (SA). In this context, the proposed approach can be viewed as a unified framework which combines several new concepts of AI in the algorithmic design. Our computational experiments with the proposed algorithm indicate that it outperforms the existing heuristics on several test problems.     

Us and them: a social capital perspective on the relationship between the business and IT departments

In this paper, a social capital perspective is applied to the relationship between the IT department and the Business organization. IT and Business are conceptualized as different occupational communities, with different understandings of their work. Our focus is on the level of social capital and the process of knowledge sharing between these occupational communities. We analyze the role that these factors play in reaching a mutual understanding within the process of IS development, and the influence this has on the perceived performance of the IT organization. Our study, combining qualitative and quantitative methods, points out that a lack of social capital (structural, relational as well as cognitive) can serve as an explanation for the often problematic relationship between these communities. Our analyses also show that social capital is especially relevant for the Business organization's perception of IT performance, whereas the IT department's perception is that performance is primarily dependent on the exchange of information.     

Fuzzy resource‐constrained project scheduling using taboo search algorithm

This paper proposes a mathematical model to deal with project scheduling problem under vagueness and a framework of a heuristic approach to fuzzy resource‐constrained project scheduling problem (F‐RCPSP) using heuristic and metaheuristic scheduling methods. Our approach is very simple to apply, and it does not require knowing the explicit form of the membership functions of the fuzzy activity times. We first identify two typical activity priority rules, namely, resource over time and minimum slack priority rules. They are used in the F‐RCPS problem and in the initial solution of Taboo search (TS) method. We improved the TS algorithm method for the solution of F‐RCPSP. Our objective is to check the performance of these rules and metaheuristic method in minimizing the project completion time for the F‐RCPS problems. In our study, we use trapezoidal fuzzy numbers (TraFNs) for activity times and activity‐on‐nodes (AON) representation and compute several project characteristics such as earliest, latest, and slack times in terms of TraFNs. The computational experiment shows that the performance of the proposed TS is better than the evaluation and light beam search algorithms in the literature. © 2012 Wiley Periodicals, Inc.     

Drivers and export performance impacts of IT capability in ‘born‐global’ firms: a cross‐national study

Past research focusing on large firms has argued that information technology (IT) capability enhances firm performance. However, these studies have seldom explored why firms develop IT capability, and have also left a void the understanding of the role of IT capability in Small‐ and medium‐sized enterprises (SMEs). This study attempts to fill that void by examining the effect of relevant environmental and firm‐level factors on IT capability, and the effect of IT capability on the export performance of Chinese and US born‐global firms, a special breed of export‐focused SMEs. Results indicate that environmental factors such as information intensity, and firm‐level factors such as international entrepreneurial orientation, prompt born‐global firms to develop IT capability. Further, our results also strongly emphasise the positive role that IT capability plays on the performance of born‐global firms. Finally, a comparative analysis of the Chinese and US born‐global firms revealed a lack of a cross‐cultural difference in the factors leading these firms to develop IT capability, therefore supporting the ‘convergence’ perspective in cross‐cultural research.     

A new method selection approach for fuzzy group multicriteria decision making

Fuzzy multicriteria decision making (MCDM) has been widely used in ranking a finite number of decision alternatives characterized by fuzzy assessments with respect to multiple criteria. In group decision settings, different fuzzy group MCDM methods often produce inconsistent ranking outcomes for the same problem. To address the ranking inconsistency problem in fuzzy group MCDM, this paper develops a new method selection approach for selecting a fuzzy group MCDM method that produces the most preferred group ranking outcome for a given problem. Based on two group averaging methods, three aggregation procedures and three defuzzification methods, 18 fuzzy group MCDM methods are developed as an illustration to solve the general fuzzy MCDM problem that requires cardinal ranking of the decision alternatives. The approach selects the group ranking outcome of a fuzzy MCDM method which has the highest consistency degree with its corresponding ranking outcomes of individual decision makers. An empirical study on the green bus fuel technology selection problem is used to illustrate how the approach works. The approach is applicable to large-scale group multicriteria decision problems where inconsistent ranking outcomes often exist between different fuzzy MCDM methods.     

Learning to rank by using multivariate adaptive regression splines and conic multivariate adaptive regression splines

Learning to rank is a supervised learning problem that aims to construct a ranking model for the given data. The most common application of learning to rank is to rank a set of documents against a query. In this work, we focus on point‐wise learning to rank, where the model learns the ranking values. Multivariate adaptive regression splines (MARS) and conic multivariate adaptive regression splines (CMARS) are supervised learning techniques that have been proven to provide successful results on various prediction problems. In this article, we investigate the effectiveness of MARS and CMARS for point‐wise learning to rank problem. The prediction performance is analyzed in comparison to three well‐known supervised learning methods, artificial neural network (ANN), support vector machine, and random forest for two datasets under a variety of metrics including accuracy, stability, and robustness. The experimental results show that MARS and ANN are effective methods for learning to rank problem and provide promising results.     

Genotype–phenotype heuristic approaches for a cutting stock problem with circular patterns

The cutting stock problem has been studied in the context of different industrial applications inducing NP-hard problems in most instances. However, the application in sawmill has not received the same attention. In this paper, we deal with the problem of determining the number of logs to cut over a period of several days and the geometry of sawmill patterns in order to satisfy the demand while minimizing the loss of material. First, the problem is formulated as an integer programming problem of the form of a constrained set covering problem where the knowledge of a priori cutting patterns is necessary to generate its columns. In our implementation, these patterns are obtained using a genetic algorithm (GA) or a simulated annealing method (SA). Then, two different approaches are introduced to solve the problem. The first approach includes two methods that combine a metaheuristic to generate the number of logs and a constructive heuristic to generate the cutting patterns for each of the logs. In the second approach, we use an exact procedure CPLEX to solve the integer programming model where the cutting patterns are generated with the GA method (GA+CPLEX) or the SA method (SA+CPLEX). These four methods are compared numerically on 11 semi-randomly generated problems similar to those found in real life. The best results for the loss are obtained with the two-stage GA+CPLEX approach that finds the best values for 7 problems.     

The other side of ranking schemes: generating weights for specified outcomes

This paper treats the problem of how to determine weights in a ranking, which will cause a selected entity to attain the highest possible position. We establish that there are two types of entities in a ranking scheme: those which can be ranked as number one and those which cannot. These two types of entities can be identified using the “ranking hull” of the data; a polyhedral set that envelops the data. Only entities with data points on the boundary of this hull can attain the number one position. There are no weights that will make an entity whose data point is in the interior of the hull to ever attain the number one position. We deal with these two types of entities separately. In the first case, we propose an approach for finding a set of weights that, under special conditions, will result in a selected entity achieving the top of the ranking without ties and without ignoring any of the attributes. For the second category of entities, we devise a procedure to guarantee that these entities will attain their highest possible position in the ranking. The first case will require using interior point methods to solve a linear program (LP). The second case involves a binary mixed integer formulation. These two mathematical programs were tested on data from a well‐known university ranking.     

Metaheuristic approaches to grouping problems in high-throughput cryopreservation operations for fish sperm

High-throughput cryopreservation operations of fish sperm is a technology being developed by researchers today. This paper first formulates a grouping problem in high-throughput cryopreservation operations of fish sperm and then develops a heuristic and four metaheuristic algorithms for its solution. The heuristic is modified from one originally proposed for the assembly line balancing problem. The four metaheuristic algorithms include simulated annealing (SA), tabu search (TS), ant colony optimization (ACO), and a hybrid differential evolution (hDE). For each metaheuristic algorithm, four different initialization methods were used. For both SA and TS, five different neighborhood solution generation methods were also studied. Real world data collected from a high-throughput cryopreservation operation was used to test the effectiveness of algorithms with different initialization and neighborhood solution generation methods. For comparison, a base line of grouping by processing order was also established. The results indicate that: (i) all algorithms performed better than the base line; (ii) using the result of the modified heuristic as the initial solution of metaheuristic algorithms lead to a better solution; the amount of improvement varied from algorithm to algorithm; (iii) among the five neighborhood solution generation operators, insertion operator was the best; (iv) among all algorithms tested, the hybrid differential evolution is the best, followed by tabu search in terms of average objective value.     

New doctors ranking system based on VIKOR method

Nowadays, we can use different websites that help us make decisions about various aspects of our lives. However, privacy protection prevents websites from providing personalised guidelines to users. We propose a novel doctor‐ranking system (DRS) based on multi‐criteria group decision‐making (MCGDM) method to address the problems of privacy protection. The following aspects differentiate our proposed DRS model from previous works: (a) textual information reviews are used to identify user preferences and complementary criteria, (b) criteria weights are determined by term frequency inverse document frequency (TF‐IDF) instead of Delphi method or expert opinion, (c) intuitionistic fuzzy sets (IFSs) are used to replace sentiment analysis to express subjective user criteria, and (d) VIsekriterijumsko KOmpromisno Rangiranjie (VIKOR) method for MCGDM with IFSs is used to solve the doctor‐ranking problem. We apply our proposed model to datasets from Haodf.com to compare the performance of our method with that of sentiment analysis and technique for order performance by similarity to ideal solution (TOPSIS) methods. The experimental results show that our method provides accurate ranking and increases the reliability of DRS.     

Assessing the values of EC and IT separately and simultaneously and inputs substitution and complement: The CES-based stochastic frontier approaches

The objective of this research is to critically explore four interrelated issues at the country level by evaluating the values of e-commerce (EC) and information technology (IT) both separately and simultaneously; examining the possibilities of complementarity and substitutability phenomena; analyzing the impacts of substitution and complement relations among ordinary capital, ordinary labor, and IT capital on the business values of EC and IT; and revisiting the productivity paradox by using the stochastic frontier approaches, which incorporate the CES production functions. The empirical results imply that it is important to assess the values of EC and IT simultaneously rather than separately.