Real Problems Research Articles

Scatter Search Algorithm for a Waste Collection Problem in an Argentine Case Study

Increasing urbanization and rising consumption rates are putting pressure on urban systems to efficiently manage Municipal Solid Waste (MSW). Waste collection, in particular, is one of the most challenging aspects of MSW management. Therefore, developing computer-aided tools to support decision-makers is crucial. In this paper, a Scatter Search algorithm is proposed to address the waste collection problem. The literature is relatively scarce in applying this algorithm, which has proven to be efficient in other routing problems, to real waste management problems. Results from real-world instances of an Argentine city demonstrate that the algorithm is competitive, obtaining, in the case of small instances, the same outcomes as those of an exact solver enhanced by valid inequalities, although requiring more computational time (as expected), and significantly improving the results of the latter for the case of larger instances, now requiring much less computational time. Thus, Scatter Search proves to be a competitive algorithm for addressing waste collection problems.

Introduction to the Special Issue

This special issue of the Journal of Benefit–Cost Analysis is dedicated to the memory of Jerry Ellig, a brilliant economist whose untimely death in 2021 cut short a productive and influential career in government and academia. Jerry was adept at applying economic concepts and empirical analysis to improve public policy, and he enjoyed not only studying real policy problems, but finding practical solutions to them. He was also a generous mentor, supporting and collaborating with graduate students and colleagues to publish prolifically in peer-reviewed economics, public administration, and political science journals, as well as law reviews and more popular outlets. He was a great communicator, able to take his academic work and translate it for different audiences, including through testimony, seminars, op-eds, short presentations, and classroom teaching. In addition to these immense talents, Jerry was genuinely kind and unpretentious; he wore Wal-Mart suits and garish ties. And he was laugh-out-loud funny, a master at diffusing difficult situations with a witty, but never mean, quip.

A new fourth-order compact finite difference method for solving Lane-Emden-Fowler type singular boundary value problems

We develop a novel fourth-order compact finite difference scheme to solve nonlinear singular ordinary differential equations. Such problems occur in many fields of science and engineering, such as studying the equilibrium of an isothermal gas sphere, reaction–diffusion in a spherical permeable catalyst, etc. These problems are challenging to solve because of their singularity or nonlinearity. By our proposed method, we can easily solve these complex problems without removing or modifying the singularity. To construct the new fourth-order compact difference method, Initially, we created a uniform mesh within the solution domain and developed a compact finite difference scheme. This scheme approximates the derivatives at the boundary nodal points to handle the problem’s singularity effectively. Employing a matrix analysis approach, we discussed the convergence analysis of the methods. To demonstrate its efficacy, we apply our approach to solve various real-life problems from the literature. The new method offers high-order accuracy with minimal grid points and provides better numerical results than the nonstandard finite difference method and exponential compact finite difference method.

Learning to Cut via Hierarchical Sequence/Set Model for Efficient Mixed-Integer Programming.

Cutting planes (cuts) play an important role in solving mixed-integer linear programs (MILPs), which formulate many important real-world applications. Cut selection heavily depends on (P1) which cuts to prefer and (P2) how many cuts to select. Although modern MILP solvers tackle (P1)-(P2) by human-designed heuristics, machine learning carries the potential to learn more effective heuristics. However, many existing learning-based methods learn which cuts to prefer, neglecting the importance of learning how many cuts to select. Moreover, we observe that (P3) what order of selected cuts to prefer significantly impacts the efficiency of MILP solvers as well. To address these challenges, we propose a novel hierarchical sequence/set model (HEM) to learn cut selection policies. Specifically, HEM is a bi-level model: (1) a higher-level module that learns how many cuts to select, (2) and a lower-level module-that formulates the cut selection as a sequence/set to sequence learning problem-to learn policies selecting an ordered subset with the cardinality determined by the higher-level module. To the best of our knowledge, HEM is the first data-driven methodology that well tackles (P1)-(P3) simultaneously. Experiments demonstrate that HEM significantly improves the efficiency of solving MILPs on eleven challenging MILP benchmarks, including two Huawei's real problems.

Fully implicit bound-preserving discontinuous Galerkin algorithm with unstructured block preconditioners for multiphase flows in porous media

Massively parallel simulation of multiphase flows in porous media is challenging due to the highly nonlinear governing equations with the complexity of various modeling features and the significant heterogeneity of material coefficients. In this paper, we introduce a fully implicit discontinuous Galerkin (DG) reservoir simulator designed for parallel computers to handle large-scale multiphase flow simulations. Our approach formulates a fully implicit DG scheme on 3D unstructured grids to discretize the nonlinear governing equations, which take into account capillary effects, permeability heterogeneity, gravity, and injection/production wells. A vertex-based slope limiter within the fully implicit DG framework is adopted to suppress oscillations near discontinuities and ensure the boundedness of the solution. We address the resulting nonlinear systems from the fully implicit discretization using a family of inexact Newton–Krylov algorithms with an analytic Jacobian. Moreover, we employ an unstructured block-type preconditioner with an efficient overlapping additive Schwarz approximation to accelerate the convergence of iterations and enhance the scalability of the simulator. Large-scale simulations of both benchmark and realistic reservoir problems on 3D unstructured grids are conducted to demonstrate the efficiency and scalability of the proposed reservoir simulator.

Smuggling and the Customs Administration in Post-Union Scotland, c. 1707–24

Smuggling plays a key role in several debates about the short- and mid-term consequences of the 1707 Union of Scotland and England, with the general consensus that smuggling was as widespread and dramatic as the early post-Union Scottish customs administration was inefficient and corrupt. This article questions these assumptions through a detailed study of the post-Union Scottish customs. By highlighting the bureaucratic sophistication apparent in the administrative changes, as well as by comparing the extent of customs fraud and tax resistance in Scotland with developments in England and Wales, the article argues for a more even-handed evaluation of the extent of smuggling on the Scottish scene. It further shows that there are good reasons why the Scottish situation was subject to an exaggerated perception in England. Ultimately, the article illustrates that the real problem for the English executive in addressing the Scottish customs in the wake of the Union was a particular fiscal dilemma that resulted from a clash between contemporary expectations about the profitability of the Scottish customs and the simultaneous need for preventive measures.

Management of Strangulated Inguinal Hernias in People Aged 60 Years and Over at the Prefectural Hospital of Kissidougou, Republic of Guinea-Conakry

Introduction: Strangulated inguinal hernias in the elderly remain a real public health problem due to their risk of intestinal necrosis leading to a high rate of morbidity and mortality. The objective of our study was to evaluate the management of strangulated inguinal hernias in people aged 60 and over at the prefectural hospital of Kissidougou. Methods: This was a retrospective descriptive study over a 3-year period from January 1, 2018 to December 31, 2020. The material consisted of all the files of patients operated on for a strangulated inguinal hernia in the elderly during the study period. Results: During this study period, we recorded 76 files of patients operated on for HIE in the elderly, i.e. a frequency of 3.34% compared to the types of hernias. The average age of our patients was 70.46 years with extremes of 60 years and 83 years. 88% of patients were male with a sex ratio of 7.4. Farmers were the most affected, i.e. 32.89%. HBP and diabetes were the main associated pathologies with 51.32% and 34.21% respectively. General anesthesia was used in all our patients. The BASSINI technique was performed in 100% of cases. The evolution was favorable in 80.26%. The case fatality rate was 3.95%. The average length of hospitalization of our patients was 8.38 days. Conclusion: Improving the prognosis of these patients would require early diagnosis and especially early management of all cases of simple inguinal hernias.

Application of Complex Fuzzy Relational Compositions to Medical Diagnosis

The capability of complex fuzzy sets plays a valuable role in resolving many real-life problems. In this paper, we present the compositions of complex fuzzy relations by using the idea of implication operators and max-product compositions of complex fuzzy relations and illustrate these compositions with concrete examples. The converse of these newly invented triangular compositions in terms of compositions of the converse relations is also defined. We also study the interactions with the union and intersection. The main goal of this article is to present a new technique to enhance medical diagnostic models that can assist in improving the features of healthcare systems. We utilize these compositions to diagnose diseases in patients on the basis of the intensity of symptoms.

Quasi-Newton iterative solution approaches for nonsmooth elliptic operators with applications to elasto-plasticity

This paper is devoted to the extension of a quasi-Newton/variable preconditioning (QNVP) method to non-smooth problems, motivated by elasto-plastic models. Two approaches are discussed: the first one is carried out via regularized approximations of the nonsmooth problem, and the second one gives an extension to nonsmooth operators in order to be applied directly. Convergence analysis is presented for both variants. Then these abstract methods are applied to elasto-plasticity where two different variants of QNVP are investigated and combined with the deflated conjugate gradient and aggregation-based algebraic multigrid methods. The convergence results are illustrated on numerical examples in 3D inspired by real-life problems, and they demonstrate that the suggested QNVP methods are competitive with the standard Newton method. Well-documented Matlab codes on elasto-plasticity are used and enriched by the suggested methods.

Bi-objective robust optimisation approach for the management of reliable emergency logistics with uncertain disruptions during a rainstorm

ABSTRACT A reliable emergency logistics system is crucial for the urban safety and public security during a rainstorm disaster. However, the impact of uncertain issues and the mitigation of psychological risks have not been well studied in the existing works. We develop a scenario-based robust optimisation approach for the emergency logistics management under uncertain disruptions. A bi-objective model, minimising total risk and cost, is formulated to decide facility locations and route plans for emergency rescue, transfer as well as materials’ transportation. The scenarios for random disruption with partial and full degrees in nodes and edges are addressed with probabilities. A psychological risk assessment model is developed to estimate the panic degree of trapped people as time varies. The complexity of the resulting mathematical model motivated the adaption and comparison of four multi-objective methods. A real-life problem in Jinzhong, China, and several tests are conducted to provide managerial insights.

Pareto Approximation Empirical Results of Energy-Aware Optimization for Precedence-Constrained Task Scheduling Considering Switching Off Completely Idle Machines

Recent advances in cloud computing, large language models, and deep learning have started a race to create massive High-Performance Computing (HPC) centers worldwide. These centers increase in energy consumption proportionally to their computing capabilities; for example, according to the top 500 organization, the HPC centers Frontier, Aurora, and Super Computer Fugaku report energy consumptions of 22,786 kW, 38,698 kW, and 29,899 kW, respectively. Currently, energy-aware scheduling is a topic of interest to many researchers. However, as far as we know, this work is the first approach considering the idle energy consumption by the HPC units and the possibility of turning off unused units entirely, driven by a quantitative objective function. We found that even when turning off unused machines, the objectives of makespan and energy consumption still conflict and, therefore, their multi-objective optimization nature. This work presents empirical results for AGEMOEA, AGEMOEA2, GWASFGA, MOCell, MOMBI, MOMBI2, NSGA2, and SMS-EMOA. The best-performing algorithm is MOCell for the 400 real scheduling problem tests. In contrast, the best-performing algorithm is GWASFGA for a small-instance synthetic testbed.

Optimization of Adaptive Sliding Mode Controllers Using Customized Metaheuristics in DC-DC Buck-Boost Converters

Metaheuristics have become popular tools for solving complex optimization problems; however, the overwhelming number of tools and the fact that many are based on metaphors rather than mathematical foundations make it difficult to choose and apply them to real engineering problems. This paper addresses this challenge by automatically designing optimization algorithms using hyper-heuristics as a master tool. Hyper-heuristics produce customized metaheuristics by combining simple heuristics, guiding a population of initially random individuals to a solution that satisfies the design criteria. As a case study, the obtained metaheuristic tunes an Adaptive Sliding Mode Controller to improve the dynamic response of a DC-DC Buck–Boost converter under various operating conditions (such as overshoot and settling time), including nonlinear disturbances. Specifically, our hyper-heuristic obtained a tailored metaheuristic composed of Genetic Crossover- and Swarm Dynamics-type operators. The goal is to build the metaheuristic solver that best fits the problem and thus find the control parameters that satisfy a predefined performance. The numerical results reveal the reliability and potential of the proposed methodology in finding suitable solutions for power converter control design. The system overshoot was reduced from 87.78% to 0.98%, and the settling time was reduced from 31.90 ms to 0.4508 ms. Furthermore, statistical analyses support our conclusions by comparing the custom metaheuristic with recognized methods such as MadDE, L-SHADE, and emerging metaheuristics. The results highlight the generated optimizer’s competitiveness, evidencing the potential of Automated Algorithm Design to develop high-performance solutions without manual intervention.

Development of a Mobile Pocket Book with a Problem-Based Learning Model to Improve Students Physics Literacy

Physics learning, especially on heat, often faces various obstacles, such as low student literacy and limited interactive learning media. Mobile pocketbooks come as one of the solutions to overcome these problems. This application-based digital learning media is designed to provide easy access to students ' learning materials through mobile devices. The mobile pocketbook is an application-based digital learning media designed to facilitate students' flexible access to learning materials through mobile devices. Using the Problem-Based Learning (PBL) model in the mobile pocketbook supports Active Learning, where students solve real problems to improve concept understanding and science literacy. This research aims to develop and test the validity and practicality of the product in the form of a mobile pocketbook as a medium to support physics learning, especially on heat material. The research method used was Research and Development (R&D) with the 4D development model (Define, Design, Develop, Disseminate). However, due to time and cost constraints, this research did not reach the dissemination stage. Product validity was evaluated through assessments from experts and practitioners. The results of the expert assessment showed a validity level of 92.50%, while the practitioner gave a validity value of 96.25%, which indicated that the product was very valid. In addition, the product practicality test was evaluated through a questionnaire given to students and teachers. The questionnaire’s results show that this media is very practical, with a practicality value from the students' response of 90.76% and the teacher reaching 96.47%. Thus, the mobile pocketbook was designed using a problem-based learning model to improve students' physics science literacy. The results showed that this media is valid and practical for enhancing students' understanding of physics material, especially the concept of heat, as evidenced by the average practicality value of 93.61%. Therefore, this mobile pocketbook is expected to be one of the learning media innovations that can improve the quality of physics learning in schools.

Profile of Problem-Solving Ability for High School Students: Context of Using PBL-Based Physics Learning Media on Global Warming

Problem-solving ability is important for students to have. This is useful for students as an effort to be able to address every problem in real life critically. This study aims to analyze students' problem-solving abilities after using physics learning media based on problem-based learning (PBL). This problem-solving ability is carried out on global warming material on the greenhouse effect. The subjects of this study were 35 students of class XI MIPA 4 at SMA N 1 Depok, Yogyakarta. The method used in this research is the descriptive analysis method. Data collection was carried out by observation and written tests. Based on the results of the analysis of students' problem-solving abilities, an average score of 75.37 was obtained in the very high category. Analysis of each indicator, including identify problems obtaining an average score of 72.22 (high category), diagnose problems obtaining an average score of 74.07 (high category), formulate strategic alternatives obtaining an average score of 79.63 (very high category). high), determine and choice strategy obtain an average score of 77.78 (very high category), and indicators evaluate the success of the strategy obtain an average score of 73.15 (high category).

Migration Securitisation and National Security in the Regional Security Complex of Nigeria–Niger Borders

Previous studies have argued that the more-than-a-year border closure has failed to curb criminal activities across Nigeria–Niger Republic borders. This stems from the intractability of criminal activities across the borders of Nigeria and the Republic of Niger. As a result, the Nigerian government securities entry and exit of foreigners from the Republic of Niger to justify its land border closure policy of 2019. The government of Nigeria claimed that border closure would address myriads of security challenges emanating from its borders with the Republic of Niger. In contention, the study raised pertinent questions such as: Is securitisation the only framework to control migration? What role could the regional security complex theory play to diagnose, comprehend and proffer solutions to cross-border security problems between Nigeria and Niger? Is migration the real security problem that the Nigerian state needs to combat? How sustainable is border security through the securitisation of migration? With the aid of a secondary source of data, the study argues that dreadful human security implications of banditry, kidnapping and pastoral conflicts across the borders are the product of amity and enmity conditions of security interdependence between Nigeria and the Niger Republic as postulated by the regional security complex theory.

Making Teaching and Learning a Collaborative Process by Adopting Research Informed Teaching on Executive Education Programmes

In a current, fast changing digital environment, the fact how fast business market is changing and how society’s perceptions evolve to become more inclusive and diverse in terms of viewpoint, and overall workforce composition is a strong indication that the education system also requires a change. To remain relevant, business and management education must reflect the realities that influence its subject matter, while at the same time addressing societal needs and expectations. Especially on the Executive Education (EE) programmes, which are driven by changes in technology, the marketplace, and the demand of individual organisation for organisation change, business schools are expected to do more than simply disseminate knowledge. Having learners or clients who are coming from a diverse range of background, who are bringing a variety of learning styles, abilities, and rich learning experience is a challenge to satisfy all stakeholders. Thus, in those programmes where we are trying to bring academic rigour and real-world experience to scale up businesses and help them growth, some innovative and inclusive ways of teaching, learning and assessment are very important to ensure learners’ personal and professional development and to demonstrate a real-world impact for those involved. This article presents a reflective analysis of introduced innovative learning, teaching, and assessment methods for one of EE programmes in one of the UK’s higher education institutions. The innovative methods employed in this course were to address the above-mentioned challenge, to demonstrate a real-world impact for those involved, in addition to ensuring learners’ personal and professional development by making teaching and learning a collaborative process. This was achieved by incorporating an active and action learning strategies in flipped classroom settings. More specifically this was achieved by introducing all elements (research led/tutored teaching, research oriented or research based) of research informed teaching, which focused on real-life problems that client companies are or were facing instead of traditional case study approach. Effectiveness of this approach was acknowledged by both colleagues, who were involved in teaching and supervisory activities and learners. Colleagues reported that learners seemed to be more enthusiastic and attentive in classes after introducing this practice. On the other hand, learners indicated that having an opportunity to work with or supervised by research active staff encourage them to conduct their own research with high quality manner. In addition, it has been observed that this practice also worked well in supervisor-learner engagement and engagement with the material especially in the flipped classroom settings. Effectiveness of the introduced methods and recommendations are based on learners’ feedback and the secondary data that demonstrates the impact for the client organisation. As this study was taken purely for the pedagogical reasons and is not conceived as pure research, at this stage study didn’t go through the ethics approval, which is an acknowledged limitation of this study, however there is an intention for farther developing this limitation to strengthen the research findings and recommendations.

Accidental exposure to blood (AEB), a real public health problem for medical and paramedical staff at the university hospital of mostaganem

Accidental exposure to blood (AEB), a real public health problem for medical and paramedical staff at the university hospital of mostaganem

Distribution of High-Risk Human Papillomavirus in Self-Collected Cervicalvaginal Samples from the General Malian Population.

Cervical cancer (CC) remains a real public health problem in low- and middle-income countries, where technical resources and competent personnel are insufficient. Persistent cervix infection by high-risk human papillomavirus (Hr-HPV) is the main cause of CC development. In the current study, we examined the distribution of Hr-HPV in the general healthy Malian population using cervicovaginal self- sampling. A total of 354 women were recruited, with a median age of 34 ± 11.37years, IQR (27-43). We found that 100% of participants agreed to self-sample at the health center. For result announcement 99.2% expressed their preference to be contacted by cell phone. Furthermore, 100% of study participants showed their willingness to undergo confirmatory CC test in case of Hr-HPV test proved positive, and to receive treatment in the event of the presence of cervical lesions. The overall prevalence of Hr-HPV was 21.2% (95% CI: 17-25.8). HPV31/35/33/52/58 with 11.9% (95% CI: 8.7-15.7) and HPV39/68/56/66 with 5.9% (95% CI: 3.7-8.9) were the most common Hr-HPV subtypes. We noted that Hr-HPV genotypes were more prevalent among women under 25years, 36.1% (N = 61). In addition, the distribution of Hr-HPV was statistically associated with age, W = 12,374, p = 0.015. Our data showed that 25.3% (N = 19) of Hr-HPV-positive women were tested positive by VIA/VILI. Among the 19 VIA/VILI-positive women, histological examination showed that 4 were CIN1, 4 were CIN2, and 2 were CIN3 grades. In addition, the median age of participants with CIN2 and CIN3 was statistically higher than the median of those with CIN1 grade, 25years IQR (21-26.75) versus 50years, IQR (40.25-55), W = 24, p = 0.009. In sum, end-users are very satisfied with the cervicovaginal self-sampling device for identifying HR-HPV genotypes as part of CC screening. In addition, it enables hospital practitioners to take the necessary action after triaging women according to their HR-HPV genotype.

Enhancing Student Engagement Through Problem-Based Learning: A Case of the Built Environment

In the rapidly evolving field of the Built Environment, traditional teaching approaches often fall short in preparing students for the complex, real-world challenges they will face in their professional careers. Problem-Based Learning (PBL) has emerged as a powerful pedagogical approach that promotes active learning and student engagement by encouraging learners to collaboratively solve real-life problems. This study explores the impact of PBL on student engagement within the Built Environment at the institutions of higher learning in particular the University of Technologies. The purpose of this research is to investigate how PBL can be effectively implemented to enhance active learning and foster deeper student engagement. This study adopted a qualitative research approach employing a systematic literature review (SLR) methodology, focusing on academic sources published between 2010 and 2024. The gathered data was synthesized using thematic analysis, wherein major themes and patterns were identified within the literature. Key themes such as collaborative learning, critical thinking, and real-world application were identified. The findings reveal that PBL not only increases student engagement but also enhances critical thinking and problem-solving skills, which are essential for success in the Built Environment sector. The study also highlights challenges, including the need for facilitator training and the development of appropriate assessment strategies to support the successful implementation of PBL. The implications of this study are significant for educators and administrators in higher education. By integrating PBL into the curriculum, the University of Technology can better prepare its students for the demands of the modern workforce, fostering a learning environment that promotes both academic excellence and practical skills development. This research contributes to the growing body of literature on active learning in higher education and provides a framework for implementing PBL in the Built Environment department, with potential applicability across other disciplines.

Statistical properties of partially observed integrated functional depths

AbstractIntegrated functional depths (IFDs) present a versatile toolbox of methods introducing notions of ordering, quantiles, and rankings into a functional data analysis context. They provide fundamental tools for nonparametric inference of infinite-dimensional data. Recently, the literature has extended IFDs to address the challenges posed by partial observability of functional data, commonly encountered in practice. That resulted in the development of partially observed integrated functional depths (POIFDs). POIFDs have demonstrated good empirical results in simulated experiments and real problems. However, there are still no theoretical results in line with the state of the art of IFDs. This article addresses this gap by providing theoretical support for POIFDs, including (i) uniform consistency of their sample versions, (ii) weak continuity with respect to the underlying probability measure, and (iii) uniform consistency for discretely observed functional data. Finally, we present a sensitivity analysis that evaluates how our theoretical results are affected by violations of the main assumptions.