Search results

The purpose of this paper is to design and implement a landmine detection robot (Venus) equipped with three electromagnetic sensors and controlled by ordered weighted averaging (OWA) sensor fusion approach. Higher numbers of detected mines in a fixed time interval and lower total power consumption are the achieved goals of this research.

OWA sensor fusion is exploited for data combination in this paper. Unlike most other landmine detection robots, Venus has three electromagnetic sensors, the positions of which can be adjusted according to the environmental conditions. Also, a novel approach for OWA weight dedication using Gaussian distribution function is applied and the whole idea is evaluated practically in several randomly mined fields. Finally, for better evaluation, performance of Venus is compared with the other two landmine detection robots.

The simulation and experimental results proved that in a predetermined interval of time, not only total energy consumption is reduced, but also by expanding the surface and the depth of influence of electromagnetic waves, the number of detected mines is considerably raised.

In contrast to the regular demining process, which is relatively expensive and complicated, the landmine detection method proposed in this research is surprisingly simple, cost effective, and efficient. Therefore, it may be attractive for every company or organization in this field of research.

The paper describes research which implements and evaluates a novel control approach based on OWA sensor fusion method, a new way of using Gaussian distribution function for determining OWA weights, and also an adaptive physical configuration for sensors based on environmental conditions.

The purpose of this paper is to comparatively examine the personnel working in the clothing sector by examining them in three different methods in order to determine the working postures, identification of the stress factors of musculoskeletal system and the exposures depending on the working postures. Methods used in the study, REBA (Hignett and McAtamney, 2000), Ovako Working Posture Analyzing System (OWAS) (Karhu et al., 1977) and PLIBEL (Kemmlert, 1995) are the scientific observation-based methods. Within the scope of this study, the working stations and the working postures of the operators who work in the clothing sector were examined and their movements that could cause harm to the body were examined and in conclusion some suggestions were suggested to prevent these movements.

Due to the standard unit of times in clothing sector are short and the work done is very repetitive, 30 min recording was thought as enough for each operator examined. These recorded videos were then divided into 30 s photographs to obtain the poses of the operators’ working postures. In the scope of the research, first, the PLIBEL observation form was filled as the PLIBEL method is more general one. According to the working postures, the body regions which are damaged or can be damaged were identified and the PLIBEL form was filled in the consideration of the risk factors in the form (Malchaire 2011). In addition, the photographs were also analyzed with REBA and OWAS methods for having more quantitative and detailed results.

The working postures of the operators who work in the cutting, sewing, ironing, quality control and packaging departments of six clothing companies were examined in the scope of this research with PLIBEL, REBA and OWAS methods in terms of ergonomy. The results belonging to each department were given separately. REBA and OWAS methods have been applied in order to investigate the working postures in more detail due to the lack of providing numerical data of the PLIBEL method. The reliability of the study has been approved with obtaining the similar results from the REBA and OWAS methods. According to Table VIII, both of the methods show that all the departments in question need ergonomic arrangements. It was analyzed that the cutting department is in the first place which needs ergonomic arrangement immediately (REBA %90.58, OWAS %87.69).

This study is composed of 65 operators who have experience between 5 and 22 years and in the age range of 22–43 working in the cutting, sewing, ironing, quality control and packaging departments in eight different clothing companies. These 65 operators were recorded by video camera during their work. The recording time were selected randomly. The movements of operators during their own work have been taken into consideration.

This paper indicates the usability of the PLIBEL, OWAS and REBA methods in clothing sector. Using these methods in clothing sectors states the value and the originality of this paper.

The aggregation of information from a group of decision experts for developing collective opinion is the important question in practice. The purpose of this paper is to provide a group decision-making method via ordered weighted aggregation (OWA) operator and grey incidence analysis.

In this study, OWA operator provides aggregation of attribute values to form an overall decision for each decision expert, and grey incidence model provides aggregation of decision experts’ evaluations to form overall score for each alternative. The example illustrates the procedure and practicability of the proposed model.

A new thought for multiple attribute group decision-making problems is given. The proposed method produces an overall desirability score for each alternative.

This is to obtain a more comprehensive and realistic solution to the given group decision-making problem. The proposed analysis method of group decision-making problems reveals vitality of grey systems theory.

This paper combines OWA operator and grey incidence analysis to obtain a novel and effective method for group decision making. It is suitable for group decision-making problems in which the attribute weights are completely unknown, expert weights are completely unknown.

The purpose of this paper is to develop a goodness index based on Hamming distance and ordered weighted averaging distance (OWAD), which is useful to make decisions. These alternative measures enrich the results of diagnostic fuzzy models and facilitate the experts’ task in decision-making. An application to a set of firms to verify the results is also presented.

The paper follows the basis of OWA operators to design a methodology to reduce the map of causes of business failure into monitoring key areas.

The present paper introduces two alternative measures to test the proposal of grouping. In the empirical application, the superiority of the minimum T-norm over other decision rules is verified. The ordered weighted averaging distance (OWAD) goodness index predicts a better adjustment over the index built using OWA and Hamming distance measures.

A useful mechanism to reduce the map of causes or diseases detected in key areas is added through this analysis. At the same time, these key areas can be disaggregated once some alert indicator is identified; this allows knowing the causes that require special attention. This application of OWA can encourage the development of suitable computer systems for monitoring the firm’s problems, alerting regarding failures and easing decision-making.

A comparison of grouping causes into key areas through a goodness index based on Hamming distance and OWAD is proposed. These contributions enrich the Vigier and Terceño (2008) model and could be applied to any model of fuzzy diagnosis to test the results.

Unnatural working postures usually cause musculoskeletal problems for workers in work field, especially in traditional industry. Many analysis and survey methodologies have been developed to identify unnatural postures and disorder risks in workplaces. The Ovako Working Posture Analyzing System (OWAS) and Nordic Musculoskeletal Questionnaire (NMQ) are the representative methods and applied widely. This study applied the both tools to investigate the work field of a manufacturing factory of the water heater’s case. We divided the manufacturing process into nine workshops, took the pictures of working motions by DV camera and analyzed the postures on OWAS. From the OWAS results, we could identify the risks level of musculoskeletal symptoms as four Action Categories (AC). And from the comparison of OWAS and NMQ results, we could provide the suggestions to improve the working methods and environment. From the results of OWAS, we found that the operators) head/neck and back were above AC3 in some workshops. If the situation continued in long period, the operators might have the risk to get musculoskeletal symptoms. From the investigation of NMQ, we also found that the percentage of aches on neck, shoulders and lower back were higher than other parts of body. The correlation between aches and jobs was more than 75 per cent. So we provided some suggestions to improve: work rotation and adjustment of work surface/height to fit in with Ergonomics. Then the risks of musculoskeletal symptoms would be reduced.

This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker.

Self-evaluation in data envelopment analysis (DEA) lacks in discrimination power among DMUs. To fix this, a cross-efficiency technique has been introduced that ranks DMUs based on peer-evaluation. Different cross-efficiency formulations such as aggressive and benevolent and neutral are available in the literature. The existing ranking approaches fail to incorporate subjective preference of “one” or “some” or “all” or “most” of the cross-efficiency evaluation formulations. Therefore, the integrated framework in this paper, based on DEA and multicriteria decision-making (MCDM), aims to present a ranking approach to incorporate different cross-efficiency formulations as well as subjective preference(s) of decision maker.

The proposed approach has an advantage that each of the aggressive, benevolent and neutral cross-efficiency formulations contribute to select the best alternative among the DMUs in a MCDM problem. Ordered weighted averaging (OWA) aggregation is applied to aggregate final cross-efficiencies and to achieve complete ranking of the DMUs. This new approach is further illustrated and compared with existing MCDM approaches like simple additive weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prove its validity in real situations.

The choice of cross-efficiency formulation(s) as per subjective preference of the decision maker and different orness levels lead to different aggregated scores and thus ranking of the DMUs accordingly. The proposed ranking approach is highly useful in real applications like R and D projects, flexible manufacturing systems, electricity distribution sector, banking industry, labor assignment and the economic environmental performances for ranking and benchmarking.

To prove the practical applicability and robustness of the proposed integrated DEA-MCDM approach, it is applied to top twelve Indian banks in terms of three inputs and two outputs for the period 2018–2019. The findings of the study (1) ensure the impact of non-performing assets (NPAs) on the ranking of the selected banks and (2) are enormously valuable for the bank experts and policy makers to consider the impact of peer-evaluation and subjective preference(s) in formulating appropriate policies to improve performance and ranks of underperformed banks in competitive scenario.

To the best of the authors’ knowledge, this is the first study that has integrated both DEA and MCDM via OWA aggregation to present a ranking approach that can incorporate different cross-efficiency formulations and subjective preference(s) of the decision maker for ranking DMUs.

The purpose of this paper is to identify new formulations for evaluating corporate social responsibility using different aggregation information operators.

The ordered weighted average (OWA) operator and its extensions, the induced OWA (IOWA) and prioritized OWA (POWA) operators are used to generate a new score for a Mexican enterprise with the corporate social responsibility (CSR) distinction.

The use of these operators allows for generation of different scenarios highlighting the relative importance of the elements. This information is useful for the government and companies to generate different evaluations depending on the specific characteristics of the region, state or municipality.

The use of aggregation operators in the traditional CSR formulation is presented. Likewise, the application of these new strategies to evaluate CSR is presented in a Mexican enterprise case to understand the steps that should be followed if the OWA operator and its extensions are to be used.

Airspace sectorization is an important task, which has a significant impact in the everyday work of air control services. Especially in recent years, because of the constant increase in air traffic, existing airspace sectorization techniques have difficulties to tackle the large air traffic volumes, creating imbalanced sectors and uneven workload distribution among sectors. The purpose of this paper is to propose a new approach to find optimal airspace sectorization balancing the traffic controller workload between sectors, subject to airspace requirements.

A constraint programming (CP) model called equitable airspace sectorization problem (EQASP) relies on ordered weighted averaging (OWA) multiagent optimization and the parallel portfolio architecture has been developed, which integrates the equity into an existing CP approach (Trandac et al., 2005). The EQASP was evaluated and compared with the method of Trandac et al. (2005), according to the quality of workload balancing between sectors and the resolution performance. The comparison was achieved using real air traffic low-altitude network data sets of French airspace for five flight information regions for 24 h a day and the Algerian airspace for three various periods (off peak hours, peak hours and 24 h).

It has been demonstrated that the proposed EQASP model, which is based on OWA multicriteria optimization method, significantly improved both the solving performance and the workload equity between sectors, while offering strong theoretical properties of the balancing requirement. Interestingly, when solving hard instances, our parallel sectorization tool can provide, at any time, a workable solution, which satisfies all geometric constraints of sectorization.

This study can be used to design well-balanced air sectors in terms of workload between control units in the strategic phase. To fulfil the airspace users’ constraints, one can refer to this study to assess the capacity of each air sector (especially the overloaded sectors) and then adjust the sector’s shape to respond to the dynamic changes in traffic patterns.

This theoretical and practical approach enables the development and support of the definition of the “Air traffic management (ATM) Concept Target” through improvements in human factors specifically (balancing workload across sectors), which contributes to raising the level of capacity, safety and efficiency (SESAR Vision of ATM 2035).

In their approach, the authors proposed an OWA-based multiagent optimization model, ensuring the search for the best equitable solution, without requiring user-defined balancing constraints, which enforce each sector to have a workload between two user-defined bounds (W_min, W_max).

The purpose of this paper is to evaluate two different asset selection methodologies and further examine these by forming optimal portfolios.

This paper deals with the problem of portfolio formation, broadly in two steps: asset selection and asset allocation by using the two different approaches for the first step and then well‐known mean variance portfolio optimization. In addition, the resulting portfolios are compared using Sharpe ratio.

The empirical observations prove the applicability of the methodology adopted in the research design, ordered weighted averaging (OWA)‐heuristic algorithm gives us a better portfolio from the sample observations. Also the asset selection procedures adopted in the research proves to be of help when an investor has to narrow down the number of assets to invest in.

The analysis provides two different methodologies for portfolio formation – though the asset allocation is based on the mean variance portfolio optimization, the asset selection methods adopted provide a systematic approach to select the efficient securities.

This paper shows that OWA can be used to decide the order of inputs for the heuristic algorithm. Also an attempt is made to use data envelopment analysis to find a solution to the problem of portfolio formation.

Since the 1980s, planning public spaces for leisure walking is largely linked with economic and cultural objectives. Parallel to this tendency and the priorities of local authorities on barker public space projects, inhabitant’s associations, that grow up after the 2000s, propose new ways of visiting the city through collective walks. Drawing on the example of the Atenistas group, and based on the discourses of its founders, its presence on social media and the narratives of participants, the purpose of this paper is to question the emergence and function of new forms of urban walking that joggle between tourism, social exchange and act of citizenship.

The case study is based on personal semi-directive interviews with organisers and participants at “Atenistas Open Walks”. It is also based on interviews that have been held with architects and urban planners within technical services of the municipality of Athens as also as within private sector’s structures.

First insights from the study question pedestrianisation as a dominant urban planning tool towards animated street life and performant local economy. Contrary to the traditional top-down approach in Athens’s public space planning which uses pedestrianisation or land management to re-invest on the city centre, Atenistas Open Walks reveal the existence of alternatives ways of a re-engagement with city values and history. People search to explore the city by themselves and re-trace their proper itineraries (and ways of seeing the city) by outpassing official discourses on the decline, the success, the dangerousness or the beautifulness of certain neighbourhoods. Consequently, walkers constantly nourish their will to better understand the city. Public space experience outpasses morphological or functional issues. The act of walking with others in the city willing to explore places and to exchange on this experience, confront people with different narratives and trajectories and can momently be a strong factor of social cohesion and activation of public space with significant impacts on local economy. Walking collectively can emerge, in this way, as a counter model of public space planning capable of revitalise not only touristic activity, but also citizenship.

The study questions dominant discourses that link urban liveability and touristic attractiveness of urban centres with recreational events and streets’ pedestrianisation projects.