In open travelling salesman subset-tour problem (OTSSP), the salesman needs to traverse a set of k (≤n) out of n cities and after visiting the last city, the salesman does not necessarily return to the central depot. The goal is to minimize the overall traversal distance of covering k cities. The OTSSP model comprises two types of problems such as subset selection and permutation of the cities. Firstly, the problem of selection takes place as the salesman’s tours do not contain all the cities. On the other hand, the next problem is about to determine the optimal sequence of the cities from the selected subset of cities. To deal with this problem efficiently, a hybrid nearest neighbor technique based crossover-free Genetic algorithm (GA) with complex mutation strategies is proposed. To the best of the author’s knowledge, this is the first hybrid GA for the OTSSP. As there are no existing studies on OTSSP yet, benchmark instances are not available for OTSSP. For computational experiments, a set of test instances is created by using TSPLIB. The extensive computational results show that the proposed algorithm is having great potential in achieving better results for the OTSSP. Our proposed GA being the first evolutionary-based algorithm that will help as the baseline for future research on OTSSP.

A simple multi-attribute decision-making method based on ranking of alternatives and attributes is proposed in this paper. The method ranks the alternatives with respect to each of the attributes based on the corresponding performance measures. Similarly, the ranks are assigned to the attributes based on their importance as perceived by the decision maker. The ranks assigned to the alternatives with respect to each of the attributes and the ranks assigned to the attributes are converted to appropriate weights and the final composite scores of the alternatives are computed using these weights. An interesting feature of the proposed method is that the qualitative attributes (i.e. the attributes expressed in linguistic terms) need not require the use of fuzzy logic. The proposed method is very simple and useful in situations of limited time availability, presence of qualitative attributes, imprecise/incomplete/partial data, and decision maker’s limited attention and capability to process the information. The proposed method is proved easier and better compared to the other widely used decision-making methods. The proposed method will be tested further on more realistic problems of the industrial environment and the results will be reported soon.

The existence of hydroelectric plants along Amazon River tributaries is a solution to satisfy the energy demand in Brazil. However, these plants are subjected to multiple risk events because of the geographic and socioeconomic characteristics of this region. In helping to address these escalating challenges, this paper presents a framework that assesses the risk events of service packs relevant to the plant. This framework presents a transparent approach for prioritizing risk events in large projects. The weights of importance of risk events are estimated using the fuzzy analytic hierarchy process. Chang’s extent analysis method takes into consideration the vagueness and imprecision of subjective human judgments. The convergence of decisions is evaluated using two aggregation approaches, namely the maximum-minimum method based on an arithmetic mean and a geometric mean. The performances of the original and modified extent analysis methods are compared using group Euclidean distance and distance between weights metrics. The degree of similarity between the evaluation metrics is examined using Spearman’s rank correlation coefficient and average overlap approaches. Due to the inconsistency of the reported results, the final rankings of the aggregation approaches are determined using a new aggregated multiple criteria decision making method. The results indicate that the original extent analysis method using the maximum-minimum method (arithmetic mean) is the best aggregation method. A Santo Antonio hydroelectric plant in Brazil is used to demonstrate the application of the proposed framework.

The characterization of project critical success factors is a multidimensional construction that relies upon numerous components. This investigation analyzes the various criteria and components that impact the accomplishment of the tasks in the human resource region of the development project. This examination utilizes a comparative method, the analytic network process method is used to recognize the significant weight of models lastly, the positioning is finished by the Technique for Order of Preference by Similarity to Ideal Solution technique, to analyze 27 critical success factors in the human resource management in project, and thinks about a wide scope of progress rules and basic achievement factors. The outcomes and assessment of specialists illustrate, select increasing trust and certainty among employees and project team managers, and it has the most effect on the accomplishment of Human Resource Management in projects. Contributing to these factors will improve the effectiveness of the activities.

In general, certified project management professionals are perceived to enhance project performance. However, this narrative has quite often been challenged in previous literature. We investigate this controversy by including professionalism and psychological capital as intervening variables. The research is based on an empirical survey of certified project managers in the region of Rawalpindi/Islamabad. 373 data samples were collected and further analyzed on the basis of critical success factor theory. The impact of project management certification along with intervening variables were hypothesized and validated to have direct and indirect relationships with project performance. Responses from certified project management professionals in the region of Rawalpindi/Islamabad support the perception but reflect that professionalism plays a supporting role between certification and performance. However, the study dismisses the role of psychological capital between professionalism and performance. We conclude that project management institutes and associations should ensure professionalism in the certification process to actually enhance project performance. The findings contribute to the body of knowledge in predicting improved project management performance by employing certified project managers with strong professional skills. Consequently, the research will help professional institutes to review the conformity of the required professional skills rather than just focusing on just passing an exam.

One of the most critical factors used to evaluate the efficiency of the portfolio selection process is the ability of the model to measure interdependencies among projects. Varieties of interactions among projects lead to several kinds of synergies in the whole portfolio, such as re-sources and knowledge interdependencies. There are few studies focused on project portfolio selection accompanied by modeling and estimating the impact of synergies between projects. Hence, this paper presents a model to select the best project portfolio applying a particular model to measure the effects of several types of interdependencies between paired projects. Then, the Promethee II method is used to prioritize projects. Then, the portfolio selection model, which is a non-linear integer model, is solved to find the best set of projects. Finally, numerical examples are addressed to illustrate the method results and validity.

This study aims to identify and evaluate the perception of major stakeholders on factors causing International Development Project (IDP) failure in the context of Afghanistan. The study adopts a quantitative cross-sectional survey research design. Thirty significant IDP failure factors included in the questionnaire were identified and shortlisted through literature reviews and validated by experts and IDP management practitioners. The survey was conducted using a structured questionnaire to investigate the most significant IDP failure factors, and various statistical tools were employed to evaluate the perception of the survey respondents. RII was used to examine the relative importance index of each failure factor. The failure factors were then grouped into five categories: Financial constraints, Ineffective recruitment, External forces, Project leadership, and Project management practices using EFA. The findings of the study will help the international development community and their IDP implementing partners, INGs and project management practitioners manage IDPs proactively and mitigate the risks of project failure. It will also contribute to the IDP management body of knowledge. The research is the first of its kind to examine the possible factors causing IDP failure in Afghanistan.

Entrepreneurial orientation is found to influence Project success along with the moderation of adaptive organizational culture and people centered management in most of the cases. This study, by addressing the moderation brings clarity to the assessment of the relation of entrepreneurial orientation dimensions on project success and is a contribution to the advancement of knowledge enhancement and improvement in Pakistan. A predominantly quantitative research strategy supported by qualitative inputs employed to obtain empirical data from 256 corporate firms in Punjab Pakistan. The gathered data examined by the structural equation modeling through Partial least square method. The results indicate that innovativeness, risk taking and proactiveness reflect the entrepreneurial orientation components. The findings of this study conclude that three dimensions of entrepreneurial orientation Innovation, Risk-taking and Proactiveness have significant and positive influence on project success. When these three dimensions of entrepreneurial orientation are moderated with adaptive organizational culture and People-Centered Management shows moderate to strong relations between different variables with a few insignificant results.

The objective of this study is to understand and evaluate the interactions of the Green Supply Chain Management enablers from a construction project's perspective in Imo State, Nigeria. This paper discusses the mix of practical intuition and determination through an interpretive structural modeling (ISM)-driven methodology. Eight (8) enablers were identified from a literature review, expert consultation, and real-world examples. While Matrice d’Impacts croisesmultipication applique a classement analysis (MICMAC) was used to identify dependence and driving power, it was used as a way to understand the relationship between the enablers. The study found that strong, yet fragile, forces drive GSCM adoption, with enhanced awareness of GSCM, increased market appeal for green construction projects, and government support through incentives and tax rebates.

The boom of real estate has been a motivating force for economic growth in India for the past few years. However, the Real Estate (RE) market of India is still in the embryonic phase and juvenile. In the context of the real estate projects, it is a general situation observed that such projects cannot meet the target as the Indian real estate companies are deficient in scientific management technology to confront the risks. The research paper aims to focus mainly on constraints and demurral of Risk Management (RM) in RE firms of India to investigate findings for the same in the Indian Real estate market and further focusing on RE projects of Ahmedabad. The paper is mostly founded on an overview of individuals who are straightforwardly or firmly identified with the administration and the RE business in India. The questionnaire survey shall be targeted over the five prime territories of Ahmedabad. This research further highlights to concerned identified primary critical risk factors (by Criticality Index Method) influencing the residential real estate market and then developing a framework for assessing the factors carrying out the quantitative analysis using various analytical methods of SPSS software, Factor analysis, ANOVA and Post-Hoc Test. The validation of the results has been done through a survey of experienced experts. The critical risks identified based on the questionnaire survey are modeled through the decision tree diagram.