Transportation is one of the most important functions of logistics management because of its impact on both the level of customer service provision and the organization’s cost structure. The study explores the transportation cost optimization strategies and how they affect the supply chain performance of Shea nuts in the Agro-processing industries in Ghana. The quantitative study design was adopted and utilized to solicit data. With a sample size of 204 respondents. Data was analyzed using multiple linear regression in Statistical Package for Social Sciences (SPSS v20). The results revealed interesting findings in the supply chain within the institution as it seeks to assert that transportation is seen to be effective and contribute highly to firms output when Agro companies use outsourcing and pooling as means of transport. From the results, the supply chain correlated positively and significantly with outsourcing and pooling as transport optimization practices in Agro firms supply chain. This paper adds to the existing literature on the supply chain systems of Agro processing firms but departs from previous studies which seek to concentrate not on the transport optimization of the Agro processing firms but rather on the challenges, production, and profit maximization of these firms. Our study is unique unlike any otheIn this research, a heterogeneous tricomposite catalyst was developed to facilitate biodiesel synthesis reaction. The Musa ABB (Kachkal) banana trunk was explored as the biowaste for the preparation of the catalyst. The trunk of the plant was cut into pieces, dried and burnt into ashes, and underwent heat treatment at 550 ℃ for 2 h. The calcined trunk was treated with potassium carbonate and CuO and the final composite was named a calcined banana trunk-K2CO3-CuO (CTKC) catalyst. The CTKC catalyst was employed in the production of rice bran pongamia oil methyl ester (RPOME) from rice bran and Pongamia pinnata (RP) oil blend in 1:1 ratio. The CTKC catalyst was characterized via XRD, and FT-IR analytical tools. Similarly, FT-IR and 1H NMR were employed to examine RP oil blend and RPOME. Under the optimized condition of 7 wt.% catalyst amount, 9:1 methanol to oil molar ratio (MTOMR), and 65 ℃ reaction temperature, the highest biodiesel yield was found to be 94.07 %. The density of RPOME was found to be 0.8811 g/cm3 which fits into the specified limit of EN 14214 and the kinematic viscosity of RPOME was found to be 3.5403 mm2/s which falls under both ASTM D6751 and EN 14214 standards. In brief, the CTKC catalyst functions as an effective heterogeneous catalyst for the synthesis of biodiesel from a binary blend of edible oil (rice bran) and non-edible oil (Pongamia pinnata). This represents an innovative strategy to tackle the rising pollution caused by diesel and petroleum-derived from fossil fuels used in vehicles. r research previously authored as it seeks to reveal the option of transport optimization that is cost effective and efficiently productive for Agro processing firms to adopt.

Sustainability is getting preference now-a-days in most of the countries in the world. This implies industrial and other developments for economic growth, and of course civilization, but certainly not at the cost of environmental degradation. Environmental conservation is a must. One of the major components of industrial sectors is their electrical energy inputs through electrical substation. Numerous research addresses the issue of energy pollution, cantering on fossil fuel. A very few research can be found which address the issue of pollution generated from electrical energy. This research addresses this issue, with special attention to electrical substations. In the last two or three decades, several electrical equipment manufacturers have started producing this equipment in Bangladesh, which were previously import-oriented. This equipment use various types of oils, acids, zinc and other metals, which are all environmentally hazardous. Thus, any industrial company, buying such equipment from substation manufacturers, should consider green aspects. As such, now it is of prime importance to select green suppliers of substation equipment. Since selection of right or green supplier involves multi-criteria evaluation, Multi-criteria Decision Making (MCDM) technique is essential. Additionally, both qualitative and quantitative criteria require fuzzy analysis to make it more precise and realistic. This research addressed the issue of environmental pollution, its sources, nature and severity, and their mitigation through selecting green suppliers.

Cities throughout the world are facing significant issues in terms of expanding urbanization. One of the key challenges is the increased amount of generated garbage and pollution due to the high demand for food and other necessities. Public waste bins are filling up faster than ever, and many of them overflow before being collected, resulting in blocked streets and unpleasant smells, as well as detrimental health and environmental effects. Overflowing garbage is a public nuisance and an eyesore, in addition to causing other health and environmental problems. Everyone desires to live in and visit places that are clean, fresh, and healthy. A smelly city with waterborne diseases and garbage all over the place does not attract visitors or investors. As a result of inefficient garbage management and recycling, cities continue to lose money and lose out on revenue advantages and job opportunities. Because of the uncertainty and complexity of garbage disposal and minimization of the environmental effect, a multi-attribute decision-making method based on a dynamic spherical fuzzy weighted average and uncertain dynamic spherical fuzzy weighted average aggregation operators are proposed to evaluate the site selection scheme of garbage disposal plant, and support for decision-making of garbage disposal site selection. In this study, firstly, spherical fuzzy information based dynamic and uncertain dynamic aggregation operators are integrated. Meanwhile, some interesting properties of the proposed operators are analyzed. Then, a multi-attribute decision-making method is established using proposed dynamic and uncertain dynamic aggregation operators under a spherical fuzzy environment. After that, a practical case on evaluating the garbage disposal site selection scheme is given to verify the effectiveness of the proposed method. The results show that this method boasts more expansive space for information representation, more flexible adaptation to the evaluation environment, and stronger robustness of the evaluation results.

Water security is a significant challenge in India due to its rapidly growing population, increasing demand for water, and frequent droughts and floods. The country has also been facing issues related to water pollution, inefficient water management practices, and limited access to safe drinking water. Ensuring water security in India requires a comprehensive approach that involves the integration of technology, policy, and community engagement to address the complex challenges associated with water management. This research paper identifies eight major challenges of water security in India, including population growth, climate change, water resource management, anthropogenic factors, technological factors, socio economic issues, geopolitical factors, and virtual water trade. Using the Analytical Hierarchy Process (AHP) method, this study ranks these challenges based on their relative importance. The findings suggest that population growth and climate change are the most critical challenges, followed by poor water resource management, anthropogenic factors, technological factors, socio economic issues, geopolitical factors, and virtual water trade. The study highlights the need for integrated and holistic approaches to address these challenges and ensure sustainable water management in India.

Sustainable crop production depends on data-driven decision-making to optimize agricultural policies. The present research evaluates the possibility of growing maize and apples in Onondaga County, New York, using a land suitability analysis based on the Analytical Hierarchical Process (AHP). The expected potential of land and empirical farmed land utilization differ significantly, according to our analysis of high-resolution soil, land use, and climate information. According to the current investigation, less than 5% of the county’s land is now under cultivation. In fact, sufficient portions appropriate for agriculture such as 44.97% suited for apple orchards and 28.66% for maize. The main obstacles to agriculture are zoning laws that restrict agricultural growth, and land use restrictions and significant forest cover. The current research stipulates modifying zoning laws and providing financial subsidies to farmers. Further, investing in infrastructure development to increase agricultural production to maximize use of agricultural land and to promote awareness for sustainable agriculture practices. The outcomes of the study highlight evidence-based strategies which help in minimizing the gap between agriculture potential and land utilization. It also promotes steady growth of agriculture by offering particular land usage administrators, agriculture scientists, and administrators with beneficial guidelines.

Energy-saving design is becoming a trending topic and top-priority over the past decades due to high energy costs, limited available resources and growing urban development. Buildings are alluded to as the major contributors of energy consumption and environmental emissions across the globe. This calls for the development of precise forecasting models of energy consumption and carbon emissions. Hence, this research paper harnesses the implementation of several contemporary metaheuristics to accurately project heating and cooling energy (HEN and CEN) in residential buildings. In this respect, black widow optimization, dandelion optimization, dingo optimization, sparrow search, and red-tailed hawk optimization are among the studied metaheuristics in this research study. The prediction accuracies of the developed models are assessed stepping on the measures of i) relative absolute error (RAE), ii) mean absolute error (MAE), iii) mean absolute percentage error (MAPE), iv) root mean squared error (RMSE) and v) Nash-Sutcliffe efficiency (NSE). It is shown that the developed red-tailed hawk optimization-based model succeeded in accomplishing the most precise results of HEN and CEN. In this context, it predicted HEN with RAE (0.201), MAE (1.838), MAPE (7.626%), RMSE (2.826), and NSE (0.921). Besides, it anticipated CEN with RAE (0.234), MAE (2.009), MAPE (7.519%), RMSE (3.246), and NSE (0.883). It can be argued that this research study could benefit architects and designers in creating more energy-efficient buildings at an early stage.

Malaysia’s food industry is facing escalating pressure from rising population demands, resource scarcity, and the mounting effects of climate change. As agriculture remains vital to national food security and economic stability, managing its environmental footprint—particularly CO₂ emissions—has become an urgent priority. Despite growing global attention to sustainability, limited empirical research has explored how internal organizational dynamics and energy transition efforts influence emissions outcomes in the Malaysian context. This study aims to address this gap by examining the effects of agriculture industry operations, renewable energy consumption, and government initiatives on CO₂ emissions management, with organizational perception acting as a mediating factor. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) on pilot survey data from food industry stakeholders, the findings highlight that organizational perception significantly mediates the relationship between renewable energy consumption and government initiatives on CO₂ emissions outcomes. While agricultural operations do not directly or indirectly influence emissions through organizational perception, both renewable energy use and proactive government policies foster a stronger environmental orientation within organizations—leading to improved emissions management. The study contributes to the discourse on sustainable development in emerging economies by emphasizing the critical role of organizational mindset in translating external sustainability drivers into tangible environmental outcomes. These insights offer practical implications for industry leaders and policymakers seeking to enhance sustainability strategies within Malaysia’s agri-food sector.

One of the utmost global trends in project management nowadays is sustainable project management (SPM), which researchers have linked to project success (PS). Hence, this paper aims to conduct systematic literature review of published articles on the effect of SPM on PS from 2013 to June 2024. By means of the Scopus database and PRISMA 2020 declaration, this study critically extracted, examined, and appraised relevant literature from the nineteen sampled papers with regard to theory, context, methodology and characteristics. From the outcomes of the content analysis, this study identified that SPM influences PS since none of them recorded a negative impact. It also concluded that the relationship is inadequately addressed from the past works. The review also enumerates future research directions and implications for practice on the correlation between SPM and PS. Overall, the conclusions of this study present a solid foundation for scholars to investigate these constructs and contribute to the extant field of information.

This study explores the imperative of profit maximization within the context of an apparel industry in Bangladesh. The research centers on the application of the Linear Programming (LP) approach along with Cost engineering and rigorous data analysis including multiple forecasting techniques to devise a systematic and quantitative strategy for maximizing profits in this multifaceted sector. The study recognizes the challenges posed by the industry's multiproduct nature and aspires to contribute valuable insights that resonate with the unique dynamics of the Bangladeshi apparel landscape. By formulating a comprehensive LP model, the research aims to address critical aspects such as resource allocation, production planning, process planning, transportation and demand considerations. The objectives extend to profit analysis based periodic forecasting of five months to assess the model's robustness, adaptability and profit pattern to dynamic business scenarios. This study shows a comparison between the profit based on the company’s present scenario and model-based analysis. Through this research, we aspire to provide a practical and accessible guide for industry practitioners, policymakers, and researchers seeking to enhance profit maximization strategies within Bangladesh's apparel industry, ultimately contributing to the sector's sustainable growth and competitiveness.

Bangladesh being one of the largest textile producers in the world, the apparel manufacturing industry has to deal with the pressure to produce the maximum possible in the face of low product quality and sustainability standards. This paper examines a case of process improvement in a Bangladeshi apparel industry, which has a middle-scale, by implementing proper use of Value Stream Mapping (VSM), which is a strong Lean Manufacturing tool. A current-state VSM was established through careful time studies and data collection of a T-shirt production line and indicated the many non-value added activities that occurred such as the high waiting time, the unbalanced workflow, and the large amount of work-in-progress (WIP) inventory. On the basis of these observations, a future-state VSM has been put forward with the incorporation of lean intervention like line balancing, standardized work, and better information flow. Future state simulation has shown that there was the possibility that the total lead time would be reduced by 35 percent and overall production efficiency to improve by 25 percent. The current study demonstrates the empirical viability of VSM in the Bangladesh apparel manufacturing industry and gives recommendations that can be implemented by factory managers and policymakers to achieve competitive advantage in the rapidly-changing international market. The paper also fills a research gap in that it portrays an empirical documented case in academia to fill the gap hitherto, in the literature of Lean implementation in the apparel and other manufacturing industries in developing countries.