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In this study, the Transit Network Design Problem (TNDP) is studied to determine the set of routes and frequency on each route for public transportation systems. To ensure the important concerns of planners like route length, route configuration, demand satisfaction, and attractiveness of the transit routes, the TNDP is solved to generate a set of routes by proposing an initial route set generation (IRSG) procedure embedded into the NSGA-II algorithm. The proposed IRSG algorithm aims to produce high-quality initial route set solutions to reach better optimization procedures. Moreover, the Multi-Objective Mixed-Integer Non-Linear Programming (MOMINLP) model is proposed to formulate the frequency setting problem on each route by minimizing the total travel time of passengers (user costs) and operator costs simultaneously, while maximizing the service coverage area near all the bus stops. The MOMINLP model is solved by applying the NSGA-II algorithm to produce a Pareto front between the first and the second objective functions. The model was applied to the Fargo-Moorhead Area (FMA), a small urban area. Results were compared with the existing transit network to measure the efficiency of the NSGA-II solution methodology. The proposed algorithm was found to considerably decrease the total travel time of passengers.

This article proposes an effective evolutionary hybrid optimization method for identifying unknown parameters in photovoltaic (PV) models based on the northern goshawk optimization algorithm (NGO) and pattern search (PS). The chaotic sequence is used to improve the exploration capability of the NGO algorithm technique while evading premature convergence. The suggested hybrid algorithm, chaotic northern goshawk, and pattern search (CNGPS), takes advantage of the chaotic NGO algorithm’s effective global search capability as well as the pattern search method’s powerful local search capability. The effectiveness of the recommended CNGPS algorithm is verified through the use of mathematical test functions, and its results are contrasted with those of a conventional NGO and other effective optimization methods. The CNGPS is then used to extract the PV parameters, and the parameter identification is defined as an objective function to be minimized based on the difference between the estimated and experimental data. The usefulness of the CNGPS for extraction parameters is evaluated using three distinct PV models: SDM, DDM, and TDM. The numerical investigates illustrate that the new algorithm may produce better optimum solutions and outperform previous approaches in the literature. The simulation results display that the novel optimization method achieves the lowest root mean square error and obtains better optima than existing methods in various solar cells.

Sustainability has emerged, arguably, as the premiere mission of contemporary architecture. Green assessment tools abound, consultancy services flourish, buildings are marketed on the basis of sustainability performance, and government, media, and corporations seem preoccupied with assessing the quality of the built environment through a green lens. Yet for all the effort, and indeed for all the progress made, fundamental issues resistant to the structural change that is essential for genuine sustainability remain. This paper reviews the state of play of sustainability across the urban landscape. It considers the road travelled so far, and points out some of the major challenges that lie ahead.

This study explores the role of information technology (IT) in supporting sustainability efforts in Saudi Arabia. Through an analysis of four case studies, we examine how technology has been implemented by Saudi Arabian companies to advance sustainability goals. The findings demonstrate a notable shift towards green initiatives in the country, with the adoption of technologies such as the Internet of Things (IoT), blockchain, and artificial intelligence. These technologies have been instrumental in enhancing energy efficiency and waste reduction. The study highlights the significance of policy interventions and public-private partnerships in achieving both environmental sustainability and economic growth. To ensure widespread adoption of sustainable practices, it is crucial for the government to focus on building digital capacity in companies and removing technological barriers. The case studies of four companies serve as illustrative examples of sustainable practices and the corresponding technological support in Saudi Arabia. The research underscores the importance of leveraging information technology and collaboration to accelerate progress towards the nation's sustainability goals.

Due to their unique nature, construction projects are considered one of the world’s most hazardous and incident-prone industrial sectors. The present study aimed to analyze health, safety and environmental (HSE) risks relating to construction projects based on the project management body of knowledge (PMBOK) and sustainability approach. This study was conducted with the participation of 30 experts, using the semi-quantitative risk assessment technique, in nine areas of the project management’s body of knowledge, based on the fuzzy analytic hierarchy process. Risk, in this study, was estimated using a two-dimensional matrix of incident probability and severity, each of which has four sub-parameters. The HSE risks pertaining to each of the nine areas of PMBOK were identified. After that, the two dimensions of risk, including incident probability and severity, were measured. Thirty-seven risk sources associated with nine areas of the PMBOK were identified. Risk analysis revealed that 20 sources were at an unacceptable risk level, and 17 risks were at a tolerable risk level. Identifying HSE-related risk sources in accordance with the nine areas of PMBOK, and using FAHP to assess the risk of these hazards in construction projects, can lead to a more realistic estimate of risk in construction projects. The presented method in the current study can create a novel perspective in terms of the construction industry’s risk management and assessment.

This study explores the impact of oil depletion on the energetic efficiency of oil extraction and refining in California. These changes are measured using energy return ratios (such as the energy return on investment, or EROI). I construct a time-varying first-order process model of energy inputs and outputs of oil extraction. The model includes factors such as oil quality, reservoir depth, enhanced recovery techniques, and water cut. This model is populated with historical data for 306 California oil fields over a 50 year period. The model focuses on the effects of resource quality decline, while technical efficiencies are modeled simply. Results indicate that the energy intensity of oil extraction in California increased significantly from 1955 to 2005. This resulted in a decline in the life-cycle EROI from 6.5 to 3.5 (measured as megajoules (MJ) delivered to final consumers per MJ primary energy invested in energy extraction, transport, and refining). Most of this decline in energy returns is due to increasing need for steam-based thermal enhanced oil recovery, with secondary effects due to conventional resource depletion (e.g., increased water cut).

The aim of this paper is to evaluate some villages in the mountain area of Sibiu County, Romania, as “smart” tourist villages. The research was carried out in two stages: Stage 1 was collection of information on (a) food products registered in different national and international quality schemes and (b) the number of tourist structures by type, comfort category, and accommodation capacity. Stage 2 was a case study conducted among 32 rural tourism entrepreneurs from 3 villages in Mărginimea Sibiului, using a questionnaire with 22 items on the criteria for evaluation of “smart” villages. The answers were systematized, statistically processed, and interpreted. The main results are as follows: (a) Concerning products, producers, and gastronomic points (PGL) registered, there are 9 products in the quality scheme “mountain product”, 10 producers on the platform “Gusturisibiene”, 1 producer of “telemea de Sibiu”, a registered product with protected geographical indication, and 2 PGL. (b) The number of officially registered tourist structures is 93, of which 72% are agritourism guesthouses. (c) The results for the evaluation of villages as “smart” are that 78.2% of locals use the internet, 74% own at least one smart device, 60.16% of energy used is renewable. There are low values of water and air pollution; there are local job and business opportunities (93.75%); future local development activities will target agriculture with all its sectors and agritourism; public administrations have implemented 7 types of activities to increase the attractiveness of localities; and quality of life, services, and social life aspects are perceived to be at high standards.

The aim of this study is to simulate the self-organized evolution mechanism of inner innovation of large-scale construction enterprises (LSCE) under different contexts. Based on NK stochastic combinatorial optimization model with two parameters (N, K), this study proposes three modules—ambidexterity, punctuated equilibrium, and automation—to simulate the change behaviors of the inner innovation system. Furthermore, this study analyses the influence of factor correlation on inner innovation performance under discusses nine different combination situations. The research results show that (a) regardless of how the relationship strength changes, fitness increases with an increasing K value; and (b) the comparison of optimization modes show that the punctuated equilibrium mode can guarantee the long- and short-term inner innovation performance LSCE. This study therefore reveals the mutual effects of the factors in the inner innovation system in LSCE and provides an effective model for internal systems analyses in the construction industry and in other sectors.