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Item type:Publication, A genetic algorithm-based method for solving multi-mode resource-constrained project scheduling problem in uncertain environment(Growing Science, 2020-01-01)Project scheduling models with resource constraints and multi-mode activities aims to create a schedule for carrying out activities considering precedence constraints and available resources in order to minimize the project duration. In the real world, we face uncertainty related to projects, where there are no historical data, hence, we should rely on the experts' judgements to estimate activity durations. For this purpose, in this paper, the 99-simulation method is used to deal with uncertainty. The exact mathematical programming model is presented in this paper and the hybrid algorithm based on Genetic Algorithm is used to solve this type of project scheduling problem which finds the near-optimal solution in a short computational time. Finally, the effectiveness of the proposed model is examined with a numerical example. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Do institutions mitigate the uncertainty effect on sovereign credit ratings?(Pontificia Universidad Católica del Perú. Departamento de Economía, 2022-07)In a more integrated economic and financial world, sovereign credit ratings have become one of the most important factors for countries that seek to access funds in the international bond market. First, we jointly analyzed institutions and uncertainty as determinants of sovereign credit ratings, and second, we tested whether strong institutions soften the impact of uncertainty. Using a sample of 74 countries from 2003 to 2020 for the major agencies Moody’s, Standard & Poor’s, and Fitch, and employing an ordered estimator approach, we find that institutions have a positive effect, whereas uncertainty has a negative effect, and the interaction between them is systematically negative. These results indicate that strong institutions reduce the negative effect of uncertainty on sovereign credit ratings. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The strengthening of corporate governance based on applied fuzzy logic(John Wiley and Sons Ltd, 2022-09-01)Despite advances in research on corporate governance, there are still knowledge gaps. The article aims to broaden the debate on strengthening corporate governance and propose a tool to facilitate decision‐making. The research is novel because of the engagement of 117 master's students from a business school, contributing to competency‐based learning on Good Corporate Governance (GCG). This is applied research with the explanatory objective and quantitative approach through modeling and simulation. The OWA Operator assesses GCG principles' adequacy and reveals a ranking of 28 enterprises listed on the Lima Stock Exchange in corporate governance, increasing transparency and reducing risks. The results indicate that six enterprises would be solid in the GCG, and the corporate governance should consider strategic capability, fair dealing, transparency, and good social responsibility practices. The main contributions are reducing the identified knowledge gaps and proposing actions to strengthen governance. The authors suggest promising lines of research.3 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Bibliometric review of research on decision models in uncertainty, 1990-2020(John Wiley and Sons Ltd, 2022-10-01)Societies experience intense and frequent changes in diverse environments, which increase uncertainty and complexity in decision-making. The decision-maker looks for alternatives to reduce risks and face these new challenges. In this context, science plays a vital role in proposing new solutions. The article aims to: (i) to carry out a bibliometric review of decision models in uncertainty through scientific mapping and performance analysis between 1990 and 2020; (ii) to know the scientific progress of 17 models that specialists validated. The Web of Science database and the VOSviewer, R, and Python software analyzed 26,835 articles in nine bibliometric indicators. The results revealed a positive trend of the publications in the analyzed models, being the Analytic Hierarchical Process the most used. Other findings showed China as the country with more scientific collaborations. There is enormous potential for future lines of research on the subject. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Socio-economic and health management of pandemics based on forgotten effects theory(Taylor & Francis, 2022-04-04)Intense and frequent changes increase uncertainty and complexity in decision-making. The COVID-19 pandemic exacerbates this situation. Therefore, the decision-maker seeks to reduce risks and meet these challenges. The manuscript aims to identify cause-effect relationships between variables affecting countries and changes caused by the COVID-19 pandemic and propose an algorithm to facilitate decision-making by identifying forgotten effects. The authors use thematic analysis to synthesize the semi-systematic literature review findings. The applied research uses a quantitative approach through modeling and simulation. The results highlight that the pandemic effects are associated with causes such as health care, political and economic stability, social justice, and the level of corruption. Decision-makers must prioritize the management of these variables guided by science. The main contribution is to show an algorithm that identifies forgotten effects in pandemics' socio-economic and health management, preventing future crises. In addition, the study advances the frontier of knowledge by addressing identified gaps and contributes to academia and policy makers. The most critical limitation is the number of variables included in this research. Future investigations could include analyses on the impact of climate change and sustainable development of nations and country-specific studies on the forgotten effects of the COVID-19 pandemic. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A multi-objective model for cooperative delivery of customer orders using multiple trucks and UAVs considering weather conditions(Elsevier BV, 2024-12-16)The increasing demand for fast, eco-friendly delivery services driven by e-commerce growth has led to innovative logistics solutions. Hybrid delivery systems combining trucks and Unmanned Aerial Vehicles (UAVs) are emerging as innovative approaches to meet these demands. This study develops a comprehensive mathematical model to optimize such systems, addressing key challenges such as UAV limitations (short range, cargo weight, and energy constraints) and the influence of weather conditions (wind speed, wind direction , and temperature). A significant contribution of this work is the simultaneous consideration of weather factors on both truck energy consumption and UAV flight performance , enabling realistic and adaptive logistics planning. In the proposed system, UAVs operate alongside trucks, returning for recharging after completing their assigned deliveries, which enhances operational feasibility. The model is designed to minimize two objectives: delivery time and cost. Small problem instances are solved using CPLEX solver for validation, while larger instances are tackled using NSGA-II and MOPSO meta-heuristic algorithms. Sensitivity analyses further explore the impact of weather parameters on system performance , offering valuable insights into its adaptability under uncertain conditions. Results demonstrate the model's effectiveness and the computational efficiency of the algorithms in handling complex, real-world scenarios, contributing to sustainable and intelligent logistics solutions.8 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A fuzzy bi-objective mathematical model for perishable medical goods supply chain network considering crisis situations: An empirical study(SAGE Publications Ltd, 2024-01-01)In case of crisis, the salvation of injuries depends on the timely provision of medical goods, relief supplies, and equipment. The aim of this study is to present a mathematical model for the supply chain network of perishable medical goods in crisis situation considering the uncertain environment. In this paper, a three-level supply chain including suppliers, intermediate warehouses, and final customers is developed for perishable medical items. The uncertainty of customer demand for service and the spent time in the intermediate warehouses are considered using the exponential distribution functions. Also, it is assumed that the life-cycle of perishable medical goods follow the Weibull distribution function. The model attempts to minimize the total costs of the supply chain and total presence time of perishable items in the whole chain. The LP-Metric method is employed for solving small-sized problems. Due to the NP-Hardness of the problem, the modified Multi-objective Particle Swarm Optimization (MOPSO) and Non-dominated Sorting Genetic Algorithm (NSGA-II) are utilized as 2 well-known and efficient meta-heuristic algorithms for solving large-sized problems. The findings indicate that the meta-heuristic algorithms are efficient in achieving close to the optimal solution for large-size problems in a reasonable time. Also, the results demonstrate that NSGA-II outperforms MOPSO in terms of the high quality solution. Finally, the applicability of the model to real-world problems is demonstrated using a real case study. This paper can assist the planners and decision-makers of perishable drugs supply chain networks in crisis conditions with on-time supplying and distributing the required emergency items.