472 research outputs found

    Performance Evaluation for the Sustainable Supply Chain Management

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    Supply chain SC activities transform natural resources, raw materials, and components into various finished products that are delivered to end customers. A high efficient SC would bring great benefits to an enterprise such as integrated resources, reduced logistics costs, improved logistics efficiency, and high quality of overall level of services. In contrast, an inefficient SC will bring additional transaction costs, information management costs, and resource waste, reduce the production capacity of all enterprises on the chain, and unsatisfactory customer relationships. So the evaluation of a SC is important for an enterprise to survive in a competitive market in a globalized business environment. Therefore, it is important to research the various methods, performance indicator systems, and technology for evaluating, monitoring, predicting, and optimizing the performance of a SC. A typical procedure of the performance evaluation (PE) of a SC is to use the established evaluation performance indicators, employ an analytical method, follow a given procedure, to carry out quantitatively or qualitatively comparative analysis to provide the objective and accurate evaluation of a SC performance in a selected operation period. Various research works have been carried out in proposing the performance indicator systems and methods for SC performance evaluations. But there are no widely accepted indicator systems that can be applied in practical SC performance evaluations due to the fact that the indicators in different systems have been defined without a common understanding of the meanings and the relationships between them, and they are nonlinear and very complicated

    Operations Management

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    Global competition has caused fundamental changes in the competitive environment of the manufacturing and service industries. Firms should develop strategic objectives that, upon achievement, result in a competitive advantage in the market place. The forces of globalization on one hand and rapidly growing marketing opportunities overseas, especially in emerging economies on the other, have led to the expansion of operations on a global scale. The book aims to cover the main topics characterizing operations management including both strategic issues and practical applications. A global environmental business including both manufacturing and services is analyzed. The book contains original research and application chapters from different perspectives. It is enriched through the analyses of case studies

    Sustainable Supply Chain Management

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    The book is a collection of studies dedicated to different perspectives of three dimensions or pillars of the sustainability of supply chain and supply chain management - economic, environmental, and social - and other aspects related to performance evaluation, optimization, and modelling of and for sustainable supply chain management, and thus presents another valuable contribution to sustainable development and sustainable way of life

    Applied Metaheuristic Computing

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    For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

    Novel approach for integrated biomass supply chain synthesis and optimisation

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    Despite looming energy crises, fossil resources are still widely used for energy and chemical production. Growing awareness of the environmental impact from fossil fuels has made sustainability one of the main focuses in research and development. Towards that end, biomass is identified as a promising renewable source of carbon that can potentially replace fossil resources in energy and chemical productions. Although many researches on converting biomass to value-added product have been done, biomass is still considered underutilised in the industry. This is mainly due to challenges in the logistic and processing network of biomass. An integrated biomass supply chain synthesis and optimisation are therefore important. Thus, the ultimate goal of this thesis is to develop a novel approach for an integrated biomass supply chain. Firstly, a multiple biomass corridor (MBC) concept is presented to integrate various biomass and processing technologies into existing biomass supply chain system in urban and developed regions. Based on this approach, a framework is developed for the synthesis of a more diversified and economical biomass supply chain system. The work is then extended to consider the centralisation and decentralisation of supply chain structure. In this manner, P-graph-aided decomposition approach (PADA) is proposed, whereby it divides the complex supply chain problem into two smaller sub-problems – the processing network is solved via mixed-integer linear programming (MILP) model, whereas the binaries-intensive logistic network configuration is determined through P-graph framework. As existing works often focus on supply chain synthesis in urban regions with well-developed infrastructure, resources integrated network (RIN) – a novel approach for the synthesis of integrated biomass supply chain in rural and remote regions is introduced to enhance rural economies. This approach incorporates multiple resources (i.e. bioresources, food commodities, rural communities’ daily needs) into the value chain and utilises inland water system as the mode of transport, making the system more economically feasible. It extends the MBC approach for technology selection and adopts vehicle routing problem (VRP) for inland water supply and delivery network. To evaluate the performance of the proposed integrated biomass supply chain system, a FANP-based (fuzzy analytical network process) sustainability assessment tool is established. A framework is proposed to derive sustainability index (SI) from pairwise comparison done by supply chain stakeholders to assess the sustainability of a system. Fuzzy limits are introduced to reduce uncertainties in human judgment while conducting the pairwise comparison. To design a sustainable integrated biomass supply chain, a FANP-aided, a novel multiple objectives optimisation framework is proposed. This approach transforms multiple objective functions into single objective function by prioritising each of the objective through the FANP framework. The multiple objectives are then normalised via max-min aggregation to ensure the trade-off between objectives is performed on the same scale. At the end of this thesis, viable future works of the whole programme is presented for consideration

    Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

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    This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors

    Improving the sustainability of coal SC in both developed and developing countries by incorporating extended exergy accounting and different carbon reduction policies

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    In the age of Industry 4.0 and global warming, it is inevitable for decision-makers to change the way they view the coal supply chain (SC). In nature, energy is the currency, and nature is the source of energy for humankind. Coal is one of the most important sources of energy which provides much-needed electricity, as well as steel and cement production. This manuscript-based PhD thesis examines the coal SC network as well as the four carbon reduction strategies and plans to develop a comprehensive model for sustainable design. Thus, the Extended Exergy Accounting (EEA) method is incorporated into a coal SC under economic order quantity (EOQ) and economic production quantity (EPQs) in an uncertain environment. Using a real case study in coal SC in Iran, four carbon reduction policies such as carbon tax (Chapter 5), carbon trade (Chapter 6), carbon cap (Chapter 7), and carbon offset (Chapter 8) are examined. Additionally, all carbon policies are compared for sustainable performance of coal SCs in some developed and developing countries (the USA, China, India, Germany, Canada, Australia, etc.) with the world's most significant coal consumption. The objective function of the four optimization models under each carbon policy is to minimize the total exergy (in Joules as opposed to Dollars/Euros) of the coal SC in each country. The models have been solved using three recent metaheuristic algorithms, including Ant lion optimizer (ALO), Lion optimization algorithm (LOA), and Whale optimization algorithm (WOA), as well as three popular ones, such as Genetic algorithm (GA), Ant colony optimization (ACO), and Simulated annealing (SA), are suggested to determine a near-optimal solution to an exergy fuzzy nonlinear integer-programming (EFNIP). Moreover, the proposed metaheuristic algorithms are validated by using an exact method (by GAMS software) in small-size test problems. Finally, through a sensitivity analysis, this dissertation compares the effects of applying different percentages of exergy parameters (capital, labor, and environmental remediation) to coal SC models in each country. Using this approach, we can determine the best carbon reduction policy and exergy percentage that leads to the most sustainable performance (the lowest total exergy per Joule). The findings of this study may enhance the related research of sustainability assessment of SC as well as assist coal enterprises in making logical and measurable decisions

    Novel approach for integrated biomass supply chain synthesis and optimisation

    Get PDF
    Despite looming energy crises, fossil resources are still widely used for energy and chemical production. Growing awareness of the environmental impact from fossil fuels has made sustainability one of the main focuses in research and development. Towards that end, biomass is identified as a promising renewable source of carbon that can potentially replace fossil resources in energy and chemical productions. Although many researches on converting biomass to value-added product have been done, biomass is still considered underutilised in the industry. This is mainly due to challenges in the logistic and processing network of biomass. An integrated biomass supply chain synthesis and optimisation are therefore important. Thus, the ultimate goal of this thesis is to develop a novel approach for an integrated biomass supply chain. Firstly, a multiple biomass corridor (MBC) concept is presented to integrate various biomass and processing technologies into existing biomass supply chain system in urban and developed regions. Based on this approach, a framework is developed for the synthesis of a more diversified and economical biomass supply chain system. The work is then extended to consider the centralisation and decentralisation of supply chain structure. In this manner, P-graph-aided decomposition approach (PADA) is proposed, whereby it divides the complex supply chain problem into two smaller sub-problems – the processing network is solved via mixed-integer linear programming (MILP) model, whereas the binaries-intensive logistic network configuration is determined through P-graph framework. As existing works often focus on supply chain synthesis in urban regions with well-developed infrastructure, resources integrated network (RIN) – a novel approach for the synthesis of integrated biomass supply chain in rural and remote regions is introduced to enhance rural economies. This approach incorporates multiple resources (i.e. bioresources, food commodities, rural communities’ daily needs) into the value chain and utilises inland water system as the mode of transport, making the system more economically feasible. It extends the MBC approach for technology selection and adopts vehicle routing problem (VRP) for inland water supply and delivery network. To evaluate the performance of the proposed integrated biomass supply chain system, a FANP-based (fuzzy analytical network process) sustainability assessment tool is established. A framework is proposed to derive sustainability index (SI) from pairwise comparison done by supply chain stakeholders to assess the sustainability of a system. Fuzzy limits are introduced to reduce uncertainties in human judgment while conducting the pairwise comparison. To design a sustainable integrated biomass supply chain, a FANP-aided, a novel multiple objectives optimisation framework is proposed. This approach transforms multiple objective functions into single objective function by prioritising each of the objective through the FANP framework. The multiple objectives are then normalised via max-min aggregation to ensure the trade-off between objectives is performed on the same scale. At the end of this thesis, viable future works of the whole programme is presented for consideration

    Applied Methuerstic computing

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    For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

    Radial Basis Function Neural Network with Particle Swarm Optimization Algorithms for Regional Logistics Demand Prediction

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    Regional logistics prediction is the key step in regional logistics planning and logistics resources rationalization. Since regional economy is the inherent and determinative factor of regional logistics demand, it is feasible to forecast regional logistics demand by investigating economic indicators which can accelerate the harmonious development of regional logistics industry and regional economy. In this paper, the PSO-RBFNN model, a radial basis function neural network (RBFNN) combined with particle swarm optimization (PSO) algorithm, is studied. The PSO-RBFNN model is trained by indicators data in a region to predict the regional logistics demand. And the corresponding results indicate the model’s applicability and potential advantages
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