Improved Artificial Bee Colony Algorithm for Solving a Single-Objective Sequence-dependent Disassembly Line Balancing Problem

<p>The welfare of the Republic of Moldova much depends on the use of its natural resources. However, the pace at which the natural resources are exploited exceeds the ability of the environment to regenerate them. Land resources are the main natural wealth of the country. The conservation and increase of effective fertility of the soils becomes the basic task of the owners of agricultural lands. The methods of the conventional agriculture do not work anymore to make the sector competitive at regional and global markets. New concepts and technologies of Green and Circular economy are of more perspective. They also are more effective under the continuous unbalanced extraction of natural resources which causes environmental damage.</p><p>The case of Moldova reflects the global trends. Some international studies have shown that the global consumption of materials per capita has doubled, while the consumption of primary energy has tripled in the last hundred years. In other words, each of us consumes three times as much energy and twice as much material as our predecessors consumed in 1900. Moreover, nowadays there are 7.2 billion consumers compared to 1.6 billion in 1900.</p><p>At the same time, the requirements for quality standards in Green economy are very high and rigid as well as  “the annual financing demand to green the global economy has been estimated to be in range 1.05 USD to 2.59 USD trillion” (UNEP, 2011). That is why the Circular ecological economy is seen as more viable solution for world, regional and national economies. ”Ecological economy” generally refers to an economy in which all the choices regarding production and consumption are made taking into account the welfare of the society and the global health of the environment. ”Circular economy” implies a system of production and consumption that generates as little loss as possible.</p><p>The EU Circular economy Package and CE Stakeholder Platform are a good start for regional economy as well as that of Republic of Moldova as its Associate Member. The beneficial solution for improving the environment of the country consists in redesigning products, production and consumption processes by minimizing waste and transforming that unused part into a resource.</p>

Human-robot collaborative disassembly line balancing considering the safe strategy in remanufacturing

The building construction materials are responsible for a large amount of energy and natural resource consumption. In light of the current challenges of resource scarcity and global climate change, the circular economy (CE) is a promising strategy to mitigate pressure on the environment, improve supplying of raw materials, and increase new market and employment opportunities. Developing eco-friendly thermal insulation materials based on agro-waste is a new waste management trend to achieve the sustainability of the resource and energy consumption in the construction sectors. In this work, banana-polystyrene composites were prepared by mixing the banana peels powder (BP) with polystyrene (PS) in different weight ratios (90:10, 80:20, 70:30, and 60:40). The physical and thermal properties such as thermal conductivity, electrical conductivity, Fourier Transform Infrared (FTIR), crystallographic structures of the fibers, X-Ray Diffraction (XRD), Thermogravimetric Analysis (TGA), and Differential Scanning Calorimetry (DSC) were carried out on BP and BP-PS1 that were prepared with ten wt.% and 20 wt.% of polystyrene powder (BP-PS2). The bio-composites results showed low thermal conductivity ranging from 0.028 to 0.030 W/m.K. The BP-PS2 exhibited a lower thermal conductivity of 0.027 W/m.K, while the pure peel powder demonstrated notable thermal stability, indicated by a total weight loss of 66.4% and a high crystallinity value of 56.1%. Furthermore, the thermal analysis (TGA) and X-Ray Diffraction (XRD) demonstrated that the pure banana peel has the highest thermal stability and crystallinity. These findings indicate that using banana peel-polystyrene composites represents an innovative solution for thermal insulation in buildings as an alternative to conventional materials to reduce energy and resource consumption.

Resource Depletion Risk for Medical Equipment: Embracing the Circular Economy.

Summary. With the continuous expansion of grid-connected power generation from renewable energy sources, such as wind and light, the forms of power sources are more diversified. The coupling and uncertainty of multiple energy sources will cause significant changes in the characteristics of the power system. Problems like the complexity of the power system lack a scientific and complete explanation. This paper comprehensively considers the regional weather conditions, the uncertainty of the output of wind and solar energy sources, and the time and space complementary characteristics of multiple power sources. Based on the theory of complex adaptive systems, a systematic and holistic optimization planning method is studied. Combining the idea of complementarity because of differences, a multipoint layout planning and design method for multienergy power systems is proposed to give full play to the synergistic effects of natural resources, achieve optimal resource allocation, and provide a theoretical basis for improving the consumption of wind and renewable energy. Taking an actual provincial power system in China as an example, through the comparison of production simulation calculations and multiscenario analysis and planning methods, the proposed method can significantly increase the consumption of wind and solar renewable energy.

In the face of escalating environmental issues and increasing consumers’ awareness, some companies put efforts towards creating a circular economy. However, insufficient consumer participation and cooperation in pro-environmental behaviour impede the creation of a circular economy. In order to deal with this problem, this article focuses on consumer behaviours and sheds light on a promising approach: anthropomorphic product design. This perspective article explains three principles of a circular economy and summarizes them in the circular economy triangle framework. Additionally, this article explores anthropomorphism, anthropomorphic marketing, anthropomorphic product designs and the relationship between anthropomorphism and pro-environmental behaviours from interdisciplinary perspectives including psychology, communication studies and marketing. Subsequently, this article explains how anthropomorphic product design helps the creation of a circular economy based on circular economic principles. Specifically, this article describes how anthropomorphic product design induces consumers to use products longer and to recycle them. Then, this article provides practical advice to derive a circular economy with anthropomorphic product designs based on schema congruity theory, construal level theory and empathy. The final section includes a summary of this article, limitations and the areas of future research. This article should contribute to the creation of a circular economy by improving the effectiveness of companies’ circular economy efforts such as waste reduction, efficient management of resources and energy consumption.

In view of the complexity and non-linearity of energy consumption system and the status quo of the development of energy in Qinghai Province,the relations between energy consumption and industrial structure is analyzed by using the quantitative analysis of grey relation degree by using the grey system theory.The relevancy degree among the primary industry,the secondary industry and the tertiary industry and living energy consumption are obtained,and then the trend of energy consumption in the following several years can be predicted.The results show that the secondary industry has the largest relevancy degree to the total energy consumption.In the end,according to the results of the research,several suggestions on how to saving energy are put forward.Firstly,the government should improve the high-tech industry and restrict the development of high-consumption and high-pollution industries.Secondly,the government should promote the low-carbon way of life;promote energy saving and control the energy consumption of the department of life.Thirdly,clean production should be actively promoted in the tertiary industry and the circular economy should be vigorously expanded.

Achieving true sustainability in the conceptualization of new building projects requires radical change compared to traditional green-field projects; circular building principles in a circular economy must become a fundamental part of the process. These principles include product recovery management, life cycle assessment (LCA), design for disassembly sequence planning, adaptability, deconstruction, closed materials loops and dematerialization. These principles recognize the importance of the End-of-Life stage in existing buildings, including adaptive reuse as an attractive alternative in a circular economy. However, the early phases of capital project delivery lack well-developed methods to: (1) decide amongst green-field construction versus adaptive reuse, (2) pre-project planning for closed-loop cycle construction and (3) plan for the optimization of the benefits of adaptive reuse. In this article, we argue that the early capital projects delivery phases for a circular economy should have distinct stages, decision gates and more appropriate planning methods, such as selective disassembly, LCA monetization protocols and optimization methods. An investigation of related studies underpins the capital project planning framework proposed and the research that must still be accomplished to enable a more circular economy in the capital projects sector.

In this paper the image compression problem is analyzed using genetic clustering algorithms based on the pixels of the image. The main problem to solve is to find an algorithm that performs the clustering efficiently. The possibility of solving clustering problems with genetic algorithms provides optimal solution. The present work makes use of genetic clustering algorithms to obtain an ordered representation of the image and then applies the DWT (Discrete Wavelet Transformation) to compress the image. The image quality is measured using PSNR measure. The genetic algorithm (GA)-based compression image has more PSNR value compared to the image without GA. It shows that the quality of the image is good for GA based compression. Also it reduces the problem of memory utilization efficiently due to compression and at the same time quality of the image is maintained due to GA. Keywords: Genetic algorithms, clustering, image compression, discrete wavelet transformation.

In the last decade, both Industry 4.0 technologies and the circular economy have expanded exponentially and they have received epistemological attention. However, there is a lack of studies about the influence that each of these technologies has on the main areas of action covered by the circular economy. This study responds to this gap by investigating the influence of the major technologies: Additive Manufacturing, Artificial Intelligence, Artificial Vision, Big Data and Advanced Analytics, Cybersecurity, Internet of Things, Robotics, and Virtual and Augmented Reality on the main areas of action covered by the circular economy. Namely, reduction of inputs consumption, reuse, recovery, recycling and reduction of waste and emissions. An initial study, based on a survey of 120 project managers, and a multiple case study of 27 projects, through 31 personal interviews and review of internal and external documentation have been conducted in order to investigate the real influence of each technology on the circular economy.Overall, the results confirm the existence of a wide range of influences that Industry 4.0 technologies offer to companies for improved circularity. These improvements are mainly related to reduce material and energy consumption, and waste and emissions generation. However, there are important differences between the potential impacts of each technology. In particular, there is most evidence of the positive impact of additive manufacturing and robotics. Likewise, the results obtained suggest the need to continue exploring the new impacts generated by the continuous development and integration of technologies.

In this paper, we describe two meta-heuristic algorithms, a discrete cuckoo search algorithm (CS) and a genetic algorithm (GA), for finding of a near optimal solution of an NP-hard combinational sequence-dependent disassembly line-balancing problem. Both algorithms use population-based evolution strategies while they have different ways in exploring a search space. GA is inspired by natural evolution concepts and the search space is explored randomly, while in CS, strategical decisions are made to explore a search space and to update the individuals in a more efficient way. A comparison between two algorithms is performed, in terms of the number of optimal solution occurrences with a number of generations, and the results clearly show that CS algorithm outperforms GA in solving the concerned problem.

In the present research, four meta-heuristic algorithms named Genetic Algorithm (GA), Gravitational Search Algorithm (GSA), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) have been used for optimal design of cascade spillway to minimize the construction cost.Usually, the traditional design methods such as Vittal and Porey (VP) method or experimental modeling are used to solve this problem leading to infeasible or near optimal solution.The main novelty of this paper is to use effective methods to solve this complex highly constrained problem.Therefore, due to unique features of meta-heuristic algorithms, these algorithms are used here to minimize the construction cost of cascade spillway as the energy dissipater structure.As the case study, cascade spillway of Tehri dam in India had been chosen.The algorithms results have been compared together and with the VP results.Comparison of the results show the effectiveness and affectivity of these algorithms to solve this optimization problem.In other words, when three-stepped spillway are considered, the results are improved with 16.16%, 16.4%, 17.73% and 17.63% respectively using GA, GSA, PSO and ABC algorithms and in the same manner, for four-stepped spillway, the results are improved 14.5%, 16.1%, 16.45% and 16.05% respectively using GA, GSA, PSO and ABC algorithms in comparison with the VP results.

Solid oxide fuel cell / electrolysis cell (SOFC / EC) can be expected as energy converters with high efficiency. In SOFC / EC material developments, the coverages of the chemical species at the three-phase boundary (TPB) are directly linked to the electrode performance. Accordingly, it is important to estimate the surface coverages at TPB to develop a new electrode. However, it is difficult to directly analyze and evaluate the coverages at the reaction field of the oxide / metal composites at high temperature (> 600 °C). Therefore, it is required to construct electrochemical kinetics with the various parameters, such as reaction constants and adsorption equilibrium constants.In order to determine the coverages at the TPB, it has demands not only to construct an appropriate electrochemical model but also both to develop a method for fitting a large number of parameters included in the model and to acquire a series of various experimental data sufficient for fitting. These requirements are not fully satisfied in previous researches [1-2]. Therefore, the chemical properties of the electrode surface have not been clarified while the reaction mechanism on the H2 electrode has been understood in FC operation.In this study, the determination method of surface coverage using an electrochemical reaction model for H2 / H2O porous electrodes composed of Ni / YSZ was established. We considered that the local equilibrium between oxygen and oxide ions is achieved in the solid electrolyte, and proposed a H2 electrode reaction model consisting of a competitive adsorption reaction as Langmuir-Hinshelwood type at TPB. Using the model, a relational expression between the electric current density and the coverage could be obtained.The equation includes the parameters of current density (i), oxygen activity (a O), the partial pressures of hydrogen (P H2) and water (P H2O), the kinetics constant of the water generation reaction at FC operation (k a), and the adsorption equilibrium constant of H, O, OH and H2O (K H, K O, K OH and K H2O). a O(eq) is the oxygen activity at equilibrium potential. The i, P H2, P H2O, a O and a O(eq) could be obtained by experimental conditions and data while ka , K H, K O, K OH and K H2O are unknown constants without appropriate fitting. The simple optimization method cannot approximate optimal solutions and determine the coverages because this model is multivariate function, which has 5 parameters.As a method for quantifying the coverage of chemical species by fitting the experimental data to the reaction model, the method using a genetic algorithm was applied. The genetic algorithm is one of the multivariable optimization methods, which efficiently approximates the optimized value of the parameters by alternation of generations created by operations composed of selection, crossover, and mutation [3]. By taking advantage of the characteristics of the genetic algorithm that randomly generates and converges initial value candidates during optimization, multiple optimal solutions can be efficiently obtained with preventing the drop to local optimum by increasing the number of trials. The most effective optimal solution could be determined from them.As the various electrochemical data for estimating the surface coverage at a temperature of 900 °C, the electrochemical data of both FC / EC under 12 conditions, in which P H2 and P H2O were changed were got using the same cell. The current interruption method was used to separate the overvoltage and ohmic voltage loss of the H2/H2O electrode during power generation and electrolysis under constant current, and then, the oxygen activity was calculated from the ohmic free-anode potential (vs. 1 atom O2). Using genetic algorithm, optimization schemes were attempted more than 50,000 times and searched for the parameter set with the smallest error between the experimental value and the estimated value from the obtained optimal solutions. The outline of the optimization process was shown in Fig. 1.As a result of fitting various reaction constants to the model with optimal solutions, the relationship between i and a O could be roughly expressed by multiple reaction rate constants and equilibrium constants, and the coverages could be quantified. Furthermore, it was possible to draw the chemical state at TPB of Ni / YSZ electrodes during FC operation.[1] W. G. Bessler et al., Phys. Chem. Chem. Phys., 12, 13888 (2010).[2] M. Ihara et al., J. Electrochem. Soc., 148(3), A209 (2001).[3] M. Srinivas et al., IEEE, 27(6), 17 (1994). Figure 1

The scheduling problem is a typical time table problem in educational administration. For such a NP complete problems, when the genetic algorithm solves this problem, it has precociousness phenomenon and quickly converges not to the global optimal solution but to the local optimal solution. Therefore, we use the advantage of local search method and partial matching crossover operation to solve TTP problem with the genetic algorithm combining search algorithm. We do a lot of experiments and evaluate the performance of the improved genetic algorithm. The experiment results show that genetic search algorithm is a more superior algorithm to apply to the TTP problem.

This paper proposes an overarching review of national municipal waste management systems and waste-to-energy as an important part of it in the context of circular economy in the selected countries in Europe. The growth of population and rising standards of living means that the consumption of goods and energy is increasing. On the one hand, consumption leads to an increase in the generation of waste. On the other hand, the correlation between increased wealth and increased energy consumption is very strong as well. Given that the average heating value of municipal solid waste (MSW) is approximately 10 MJ/kg, it seems logical to use waste as a source of energy. Traditionally, waste-to-energy (WtE) has been associated with incineration. Yet, the term is much broader, embracing various waste treatment processes generating energy (for instance, in the form of electricity and/or heat or producing a waste-derived fuel). Turning waste into energy can be one key to a circular economy enabling the value of products, materials, and resources to be maintained on the market for as long as possible, minimising waste and resource use. As the circular economy is at the top of the EU agenda, all Member States of the EU (including the EEA countries) should move away from the old-fashioned disposal of waste to a more intelligent waste treatment encompassing the circular economy approach in their waste policies. Therefore, the article examines how these EU policies are implemented in practice. Given that WtE traditionally is attached to the MSW management and organisation, the focus of this article is twofold. Firstly, it aims to identify the different practices of municipal waste management employed in selected countries and their approaches in embracing the circular economy and, secondly, the extent to which WtE technologies play any role in this context. The following countries, Estonia, Greece, Italy, Latvia, Lithuania, Norway, Poland, Slovenia, Spain, and the UK were chosen to depict a broad European context.