Minimizing environmental footprint in FDM additive manufacturing: Analyzing process efficiency through advanced optimization techniques

Watershed prioritization using morphometric analysis by MCDM approaches

Dam site selection is an important task in water resource management and it depends on a number of biophysical as well as socio-economic factors. Dam site selection is becoming important research area due to the increase of water scarcity and also to prevent flood in certain area. This paper presents Multi Criteria Decision Making (MCDM) approach in water resources management through the integration of Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). These methods were applied for identification of suitable dam site in Tlawng sub-basin. The influential criteria for dam site selection were initially identified through literature review and experts opinion which was followed by the selection of four (4) feasible sites after having studied Tlawng watershed. Lastly, AHP and TOPSIS were applied to determine the relative weight and rank respectively.

In software defect prediction systems, choosing the best data mining classification algorithm is essential for efficient decision-making. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for ranking classification algorithms according to several criteria is assessed in this study. Classifiers were evaluated and ranked using the AR1 and JM1 datasets using a structured multi-criteria decision-making (MCDM) methodology. According to the results, Lazy-IBK continuously performs better than other classifiers, demonstrating how well TOPSIS finds the top-performing models. Furthermore, the comparative study of classification algorithms shows how reliable the approach is when taking into account variables like scalability, accuracy, and computational efficiency. According to the results, TOPSIS considerably enhances classifier selection when it comes to software defect prediction, resulting in data mining applications that make better-informed and impartial decisions. Key Words: MCDM, Software Defect Prediction, TOPSIS

PurposeThe purpose of this study is to provide a decision support tool to deal with the problem of seting priorites among patients competing for limited health care resources. Limited resources and unlimited demands prevent health-care services to be provided to all those in need. This became publicity evident with the current Covid-19 pandemic. Although controversial, health care rationing has always existed and is now inevitable. Setting priorities becomes then inevitable. How to define those priorities is a complex and yet irresolvable issue mainly because it involves several and conflicting criteria, translated into efficiency and equity considerations. This is why multi-criteria decision analysis (MCDA) was introduced to health care as an appropriate decision-support framework for solving complex problems.Design/methodology/approachThis paper proposes the application of two combined approaches – analytic hierarchy process (AHP)-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and AHP-VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), as decision support tools to rank patients with competing needs in a more effective and equitable way. A rationing scenario involving four patients, differentiated by personal characteristics and health conditions, is used to illustrate, test and compare the applicability of both approaches. After extraction of the relative weights of the prioritization criteria involved in the hypothetical scenario from paired wise comparison methods, TOPSIS and VIKOR priority setting methods were designed.FindingsResults suggest that patients ranking from both combination approaches are similar and in accordance with the order made directly by health-care professionals. Therefore, the relative weights computed by AHP in combination with TOPSIS and/or VIKOR methods could be used with suitable applicability by health-care decision-makers.Originality/valueThis study is the first attempt to apply a combination of MCDA methods to patients’ prioritization context and the first to cross previous studies to deepen and consolidate the research.

The application of multiple criteria decision-making (MCDM) techniques in real-life problems has increased in recent years. The need to build advanced decision models with higher capabilities that can support decision-making in a broad spectrum of applications, promotes the integration of MCDM techniques with applicable systems, including artificial intelligence, and Geographic Information Systems (GIS). The Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are among the most widely adopted MCDM techniques capable of resolving water resources challenges. A critical problem associated with water resource management is dam site selection. This paper presents a comparative analysis of TOPSIS and AHP in the context of decision-making using GIS for dam site selection. The comparison was made based on geographic and water quality criteria. The geographical criteria are geology, land use, sediment, erosion, slope, groundwater, and discharge. The water quality criteria include Soluble Sodium Percentage, Total Dissolved Solid, Potential of Hydrogen, and Electrical Conductivity of water. A ratio estimation procedure was used to determine the weights of these criteria. Both methods were applied for selection of optimal sites for dams in the Sistan and Baluchestan province, Iran. The results show that the TOPSIS method is better suited to the problem of dam site selection for this study area. Actual locations of dams constructed in the area were used to verify the results of both methods.

The multi-criteria decision-making (MCDM) method often entails a number of steps, such as identifying the decision problem, defining the criteria, calculating the weighting of the criteria, assessing the alternatives against the criteria, and finally choosing the best alternative based on the overall evaluation. In this paper, the essential factor for sports, politics, journalism or media, and technological empowerment of women in India are found by MCDM techniques, which may also be utilized to examine the key factors influencing women’s empowerment. The uses the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) MCDM methodologies are taken to discover the optimal criteria for empowerment. The decision-making for finding the factors is done by taking multi experts’ opinions. First, determined the best criteria among the six criterion’s, such as Family Support (C1), Financial Support (C2), Cultural and Religious Barrier (C3), Child Marriage (C4), Nutrition (C5), and Shame and concealment (C6). The weights are calculated by the AHP method. According to the importance of the criteria, select a significant alternative for empowering women in many fields. Also take six possibilities into consideration, which are Empowerment in Sports (A1), Empowerment in Politics (A2), Empowerment in Administrative Service (A3), Empowerment of Journalism or Media (A4), Empowerment for Social Work (A5) and Empowerment of Technological (A6) and they are ranked by TOPSIS method. To verify the validity and robustness of our result, sensitivity analysis is performed by removing some criteria to make sure the procedure is reliable and a comparative study using a fuzzy environment.

Appropriate tree fertilization with essential nutrients is considered as one of the major factors in enhancing the quality and quantity of horticultural crops. The most efficient way to fertilize trees is to dig holes around the trunks and fill them with appropriate chemical and organic fertilizer. Doing this operation with mechanized methods reduces costs and increases productivity compared to traditional methods. In the present study, multi‐criteria decision‐making (MCDM) methods, including deterministic analytical hierarchy process (AHP) and fuzzy analytical hierarchy process (FAHP), technique for order of preference by similarity to ideal solution (TOPSIS), fuzzy TOPSIS (FTOPSIS), and analytic network process (ANP), were used to score and select the appropriate fertilizing method for apple trees based on the growers and expert's perspectives. The criteria, including fertilizing operation cost, crop yield, the percentage of tree damages, ease of entering and moving fertilizing equipment in tree rows, field capacity (with or without machinery), comfort and safety of fertilizing operations, after‐sales service, access to the required machinery and implements, crop selling price, and crop quality, were used in the above‐mentioned methods. The fertilization methods (Hole digging) considered in the present study were traditional fertilization (Shovel), orchard Trencher, motor hole digger, fixed centerline tractor‐mounted hole digger, and off‐set tractor‐mounted hole digger. Based on the results, the priority of mechanized fertilizing methods was determined as tractor‐mounted hole diggers (AHP weight of 0.286, FAHP weight of 0.285, TOPSIS relative proximity of 0.65, and FTOPSIS relative proximity of 0.64), fixed centerline tractor‐mounted hole diggers (AHP weight of 0.219, FAHP weight of 0.158, TOPSIS relative proximity of 0.56, and FTOPSIS relative proximity of 0.62), motor hole diggers (AHP weight of 0.171, FAHP weight of 0.079, TOPSIS relative proximity of 0.46, and FTOPSIS relative proximity of 0.31), and orchard trenchers (AHP weight of 0.12, FAHP weight of 0.057, TOPSIS relative proximity of 0.19, and FTOPSIS relative proximity of 0.20), respectively. Based on the ANP method, off‐set and fixed centerline tractor‐mounted hole diggers had the highest priority (weights of 0.43 and 0.27), followed by trencher (weight of 0.16), motor hole diggers (weight of 0.09), and the traditional method (weight of 0.04). Results showed that applying orchard tractors equipped with mounted diggers, especially off‐set types, can play an important role in enhancing the quantity and quality of apples produced, as well as reducing the costs of fertilizing operations.

Application of AHP, TOPSIS, and TFNs to plant selection for phytoremediation of petroleum-contaminated soils in shale gas and oil fields

Penelitian ini bertujuan untuk merancang dan mengimplementasikan Executive Support System (ESS) yang efektif menggunakan metode Simple Additive Weighting (SAW), Analytic Hierarchy Process (AHP), dan Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) dalam konteks perencanaan strategis. Kemampuan ESS dalam mendukung pengambilan keputusan eksekutif dihadapkan pada kompleksitas faktor dan kriteria yang melibatkan banyak aspek bisnis. Metode SAW digunakan untuk memberikan nilai relatif pada setiap kriteria, memberikan pendekatan yang sederhana dan mudah dimengerti. AHP digunakan untuk menangani penilaian kriteria secara hierarkis, memungkinkan penetapan bobot yang lebih akurat berdasarkan tingkat hierarki kriteria. TOPSIS digunakan untuk memilih alternatif terbaik dengan mempertimbangkan kedekatan dengan solusi ideal. Penelitian ini adalah penelitian kuantitatif dengan menggunakan metode kepustaakaan. Hasil penelitian menunjukkan bahwa integrasi metode SAW, AHP, dan TOPSIS dalam ESS memberikan kontribusi positif dalam meningkatkan kemampuan sistem dalam memberikan dukungan yang lebih optimal bagi pengambilan keputusan eksekutif. Kesederhanaan SAW, penilaian hierarkis AHP, dan ketepatan pemilihan TOPSIS bekerja bersama untuk memberikan solusi yang akurat dan efisien.

This study aimed to develop alternative materials and technologies for making canting stamps used in producing batik canting (stamped batik) to transfer hot wax from the pan to the fabric. Previous researchers have studied materials such as wood, aluminum, multiplex, acrylic, and acrylonitrile butadiene styrene (ABS). Manufacturing technologies have also been analyzed, including manual manufacturing, computer numerical control (CNC) milling, laser cutting, and additive manufacturing. However, none of these materials and technologies were considered suitable alternatives for copper canting stamps. This paper proposes Conductive ABS-Electroformed By Copper (CABS-EBC) through additive manufacturing and electroforming processes as alternative material for canting stamps. A multi-criteria decision-making (MCDM) approach was used to assess alternative materials and technologies. The alternatives and criteria were calculated using the Simple Additive Weighting (SAW), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Preference Ranking Organization Method of Enrichment Evaluation (PROMETHEE) techniques. Besides this, assessment was also carried out based on expert opinions. The results showed that copper was the most suitable material, with Closeness = 1.000, Yi = 0.995, and Phi = +1.00. Meanwhile, CABS-EBC ranked second, with Closeness = 0.627, Yi = 0.864, and Phi = +0.50. The selected technology was additive manufacturing combined with electroforming, with Closeness = 0.700, Yi = 0.895, and Phi = +0.39. By using MCDM on the material-technology development candidates it was found that CABS-EBC processed with additive manufacturing is capable of substituting copper as a canting stamp material. It is expected that the production capacity of the traditional manufacturing process can be enhanced by adopting these new materials and technologies.

Population of the world is increasing day by day, resulting in enormous amount of waste production. In the modern age of great technological advancements, there needs to be a systematic method to keep the environment clean. The waste management activities, i.e., collection, transport and disposal, pose a great challenge to the waste managers as they have to factor in various eclectic factors such as land availability, facilities available, budget, time required and the impact it would have on the environment, while tackling this problem. Lahore, despite being the most developed city of Pakistan, does not have a suitable solid waste management system. An increasing population leads to more waste generation, and in Lahore the situation is no different. Several waste management companies are working in the city, but as of yet they have not been able to make significant inroads to completely eradicate the problem. The aim of this paper is to suggest a suitable way for dealing with the waste. To accomplish this aim, a hierarchy-based model is used, considering six criteria and five alternatives. We used multi-criteria decision analysis to decide among different waste management alternatives. Forecasting has been used to find the population and waste produced over the years. Analytical hierarchy process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are used to rank the feasible alternative. The results show that the population and waste were increasing drastically. Aerobic digestion was ranked as the best alternative for waste management according to AHP and TOPSIS, but there is great variation among the rank of other alternatives.

The importance of disaster logistics and its share in the logistics sector are increasing significantly. Most disasters are difficult to predict; therefore, a set of measures seems to be necessary to reduce the risks. Thus, disaster logistics needs to be designed with the pre-disaster and post-disaster measures. These disasters are experienced intensely in Turkey and the importance of these measures becomes more evidential. Therefore, accurate models are required to develop an effective disaster preparedness system. One of the most important decisions to increase the preparedness is to locate the centres for handling material inventory. In this context, this paper analyses the response phase designing the disaster distribution centres in Turkey at the provincial level. AHP (Analytical Hierarchy Process) based TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method and goal programming model integration is used to decide alternative locations of distribution centres. TOPSIS method is employed for ranking the locations, which is based on hazard scores, total area, population, and distance to centre. Two conflicting objectives are first proposed in the goal programming formulation, in which maximization of the TOPSIS scores and minimization of the number of distribution centres covering all demands named set covering model are included. Although Gecimli has the highest priority with 0.8 p score in the TOPSIS ranking, Altincevre (0.77) and Buzlupınar (0.75) ensure both the TOPSIS score and coverage of the demand nodes. The results from this paper confirm that the computational results ensure disaster prevention insights especially in regions with limited data.

<p>One common multi-criteria decision making (MCDM) technique is the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is frequently applied in several application fields. Finding an ideal and an anti-ideal solution, which are then utilized to determine the distances between the alternatives and the ideal solution, is the foundation of the TOPSIS approach. The method then ranks the alternatives according to their closeness to the ideal solution. TOPSIS is able to handle both quantitative and qualitative criteria, however, the method can be sensitive to the weight of the criteria, and the ranking results can be influenced by the choice of the reference alternatives. This paper provides an overview of the TOPSIS method, its applications, main characteristics and limitations. The paper also provides step-by-step instructions on how to apply the TOPSIS method, including the determination of the criteria weights, the construction of the decision matrix, and the calculation of the TOPSIS scores.</p>

Multi Criteria Decision Making (MCDM) helps decision makers (DMs) solve highly complex problems. Accordingly, MCDM has been widely used by DMs from various fields as an effective and reliable tool for solving various problems, such as in site and supplier selection, ranking and assessment. This work presents an in-depth survey of past and recent MCDM techniques cited in the literature. These techniques are mainly categorised into pairwise comparison, outranking and distance-based approaches. Some well-known MCDM methods include the Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), Elimination et Choix Traduisant la Realité (ELECTRE), Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Each of these methods is unique and has been used in a vast field of interest to support DMs in solving complex problems. For a complete survey, discussions related to previous issues and challenges and the current implementation of MCDM are also presented.

Experimental investigation and optimization of cobalt bonded tungsten carbide composite by hybrid AHP-TOPSIS approach