Optimum layout design of onshore wind farms considering stochastic loading

Renewable energy technologies are developing rapidly, while in the last decade great interest is encountered in the use of wind energy, especially due to the energy crisis and serious environmental problems appeared from the use of fossil fuels and therefore a large number of wind farms have been installed around the world. On the other hand the ability of nature inspired algorithms to efficiently handle combinatorial optimization problems was proved by their successful implementation in many fields of engineering sciences. In this study, a new problem formulation for the optimum layout design of onshore wind farms is presented, where the wind load is implemented using stochastic fields. For this purpose, a metaheuristic search algorithm based on a discrete variant of the harmony search method is used for solving the problem at hand. The farm layout problem is by nature a constrained optimization problem, and the contribution of the wake effects is significant; therefore, in two formulations presented in this study the influence of wind direction is also taken into account and compared with the scenario that the wake effect is ignored. The results of this study proved the applicability of the proposed formulations and the efficiency of combining metaheuristic optimization with stochastic wind loading for dealing with the problem of optimal layout design of wind farms.     

Bi-objective optimisation model for installation scheduling in offshore wind farms

A bi-objective optimisation using a compromise programming approach is proposed for installation scheduling of an offshore wind farm. As the installation cost and the completion period of the installation are important aspects in the construction of an offshore wind farm, the proposed method is used to deal with those conflicting objectives. We develop a mathematical model using integer linear programming (ILP) to determine the optimal installation schedule considering several constraints such as weather condition and the availability of vessels. We suggest two approaches to deal with the multi-objective installation scheduling problem, namely compromise programming with exact method and with metaheuristic techniques. In the exact method the problem is solved by CPLEX whereas in the metaheuristic approach we propose Variable Neighbourhood Search (VNS) and Simulated Annealing (SA). Moreover, greedy algorithms and a local search for solving the scheduling problem are introduced. Two generated datasets are used for testing our approaches. The computational experiments show that the proposed metaheuristic approaches produce interesting results as the optimal solution for some cases is obtained.     

进化计算在复杂机电系统设计自动化中的应用综述

复杂机电系统设计自动化是知识自动化的一个重要分支, 在机器人系统设计、高档数控机床设计、智能装备系统设计等方面具有重要的研究意义和应用价值. 本文对进化计算在复杂机电系统设计自动化中的应用进行了综述. 首先, 介绍了几种常用进化计算方法及其优点; 其次, 对进化计算在电子系统、微机电系统和复杂机电系统三个领域的设计自动化进行了较为系统且全面的总结. 然后, 以一类典型的复杂机电系统—机器人系统的设计自动化为代表, 对进化计算在机器人系统设计自动化的研究发展进行了讨论. 最后, 针对进化计算在复杂机电系统设计自动化中存在的共性关键问题进行了讨论与展望.     

Application of evolutionary computation for rule discovery in stock algorithmic trading: A literature review

Despite the wide application of evolutionary computation (EC) techniques to rule discovery in stock algorithmic trading (AT), a comprehensive literature review on this topic is unavailable. Therefore, this paper aims to provide the first systematic literature review on the state-of-the-art application of EC techniques for rule discovery in stock AT. Out of 650 articles published before 2013 (inclusive), 51 relevant articles from 24 journals were confirmed. These papers were reviewed and grouped into three analytical method categories (fundamental analysis, technical analysis, and blending analysis) and three EC technique categories (evolutionary algorithm, swarm intelligence, and hybrid EC techniques). A significant bias toward the applications of genetic algorithm-based (GA) and genetic programming-based (GP) techniques in technical trading rule discovery is observed. Other EC techniques and fundamental analysis lack sufficient study. Furthermore, we summarize the information on the evaluation scheme of selected papers and particularly analyze the researches which compare their models with buy and hold strategy (B&H). We observe an interesting phenomenon where most of the existing techniques perform effectively in the downtrend and poorly in the uptrend, and considering the distribution of research in the classification framework, we suggest that this phenomenon can be attributed to the inclination of factor selections and problem in transaction cost selections. We also observe the significant influence of the transaction cost change on the margins of excess return. Other influenced factors are also presented in detail. The absence of ways for market trend prediction and the selection of transaction cost are two major limitations of the studies reviewed. In addition, the combination of trading rule discovery techniques and portfolio selection is a major research gap. Our review reveals the research focus and gaps in applying EC techniques for rule discovery in stock AT and suggests a roadmap for future research.     

An augmented self-adaptive parameter control in evolutionary computation: A case study for the berth scheduling problem

The demand for international seaborne trade has substantially increased over the last three decades and is predicted to continue increasing during the upcoming years. A marine container terminal, as an important node in supply chains, should be able to successfully cope with increasing demand volumes. Berth scheduling can significantly influence the general throughput of marine container terminals. In this study, a mixed-integer linear programming mathematical model is proposed for the berth scheduling problem, aiming to minimize the summation of waiting costs, handling costs, and late departure costs of the vessels that are to be served at a marine container terminal. An innovative Evolutionary Algorithm is designed to solve the developed mathematical model. The proposed solution algorithm relies on the augmented self-adaptive parameter control strategy, which is developed in order to effectively change the algorithmic parameters throughout the search process. Performance of the designed algorithm is evaluated against nine alternative state-of-the-art metaheuristic-based algorithms, which have been frequently used for berth scheduling in the marine container terminal operations literature. The results demonstrate that all the developed algorithms have a high level of stability and return competitive solutions at convergence. The computational experiments also prove superiority of the designed augmented self-adaptive Evolutionary Algorithm over the alternative algorithms in terms of different performance indicators.     

Ubiquitous conceptual design of a ubiquitous application: A textile SME case study for real time manufacturing monitoring

Advances in Information and Communication Technologies (ICT), computing, networking, mechanics and electronics are changing the people’s way of life. Several research efforts are leading the design and development of Artifact and Service Combination (ASC) with the implementation of Ubiquitous Technologies (UTs) in multidisciplinary sectors. However, the design process of such systems often ends in the implementation of conventional approaches and tools. A Ubiquitous Design Support Environment (UDSE) comprising an application intended to guide the different activities, tools and resources applied at the conceptual design stage is presented. After needs analysis, multidisciplinary collaborations are also required in order to generate innovative conceptual solutions, focusing this approach in the conceptual design stage of traditional design methods. Some activities from the conceptual design stage are enhanced through the use of the UDSE as well as through the use of a novel ubiquity assessment tool for concept selection and validation of Ubiquitous Products and Services. Finally, a case study on a Small and Medium Enterprise (SME) from textile sector, in a developing country, is presented to analyze and validate the presented concepts.     

The inhibitors of risk information sharing in the supply chain: A multiple case study in Turkey

One of the greatest threats faced by organizations is disruption in the supply chain arising from not sharing risk information among the supply chain partners. The aim of this study is to identify the inhibitors of risk information sharing in a supply chain by using practical‐side evidence. An exploratory multiple case design was utilized to investigate why supply chain partners in Turkey may be reluctant to share risk information among their members and provide solutions to overcome these barriers. The results of the study indicate that the inhibitors of risk information sharing fall into three categories: risk‐related, organization‐related, and management‐related. Furthermore, the findings demonstrate possible solutions for reluctance in risk information sharing among supply chain partners based on managers' experiences.     

User engagement in e-government systems implementation: A comparative case study of two Singaporean e-government initiatives

Noting that user engagement is a key issue in e-government systems implementation and that the actual form and strategies of user engagement, especially within the context of e-government, is poorly defined, this paper intends to contribute to the research and practice of e-government systems implementation by conducting a comparative case study of two e-government systems implementation within a single government agency in Singapore. The comparative analysis of these two e-government systems implementation was accomplished through using stakeholder theory as a sense-making theoretical lens. This generated four findings pertaining to the form and strategies of user engagement in e-government systems implementation.     

Exploring vendor capabilities in the cloud environment: A case study of Alibaba Cloud Computing

Cloud computing is being viewed as an effective enabler for enhanced operational efficiency and flexibility in competitive business environments. Despite the increased knowledge on cloud computing, very few studies have been conducted to explore vendors' capabilities for service development and delivery. This gap prevents us from developing a full understanding of the service provision process and the actions through which vendors develop cloud services and create value for clients. In this paper, we present an in-depth qualitative case study of Alibaba Cloud Computing, China’s biggest Infrastructure-as-a-Service (IaaS) vendor, and identify five important capabilities, namely, cloud platform development, cloud platform deployment, IaaS imitation, IaaS commercialization, and IaaS improvement. We suggest that these capabilities and the associated actions are central to vendors’ adoption of cloud computing, acquisition of knowledge, and delivery and improvement of their cloud service provision. This paper contributes incrementally to the evolving scholarship on cloud computing and also offers useful guidelines for current and aspiring vendors.     

A step-by-step performance assessment and improvement method for ERP implementation: Action case studies in Chinese companies

The implementation of enterprise resource planning (ERP) is a complex process, and the failure rate remains very high. The literature has reported over 80 critical success factors for ERP implementation, but companies typically do not know to exploit them. In this article, a step-by-step assessment and improvement method for ERP implementation is proposed and applied in three companies. First, a five-stage ERP implementation model is proposed. Second, about 80 critical success factors (CSFs) from the literature are elaborated into key performance indices (KPIs), which are associated with each stage of ERP implementation by ten local ERP experts. Third, the weights of the KPIs are calculated using the Dumpster–Shafer method and the evaluation of ten experts. During the implementation process, performance is measured at each stage and remedial actions are identified if the performance is below expectation. An implementation flowchart is developed based on a five-stage model and the philosophy of continuous improvement. Three action cases in Chinese manufacturing companies are conducted to illustrate the effects of the assessment model, which is also currently being used by a consulting company specialising in ERP implementation. With further evaluation by local experts, the model has the potential to serve as a guideline for ERP implementation in other countries.     

An analysis of the interface between evolutionary algorithm operators and problem features for water resources problems. A case study in water distribution network design

Evolutionary Algorithms (EAs) have been widely employed to solve water resources problems for nearly two decades with much success. However, recent research in hyperheuristics has raised the possibility of developing optimisers that adapt to the characteristics of the problem being solved. In order to select appropriate operators for such optimisers it is necessary to first understand the interaction between operator and problem. This paper explores the concept of EA operator behaviour in real world applications through the empirical study of performance using water distribution networks (WDN) as a case study. Artificial networks are created to embody specific WDN features which are then used to evaluate the impact of network features on operator performance. The method extracts key attributes of the problem which are encapsulated in the natural features of a WDN, such as topologies and assets, on which different EA operators can be tested. The method is demonstrated using small exemplar networks designed specifically so that they isolate individual features. A set of operators are tested on these artificial networks and their behaviour characterised. This process provides a systematic and quantitative approach to establishing detailed information about an algorithm's suitability to optimise certain types of problem. The experiment is then repeated on real-world inspired networks and the results are shown to fit with the expected results.     

Designing for ethical innovation: A case study on ELSI co-design in emergency

The ever more pervasive ‘informationalization’ of crisis management and response brings both unprecedented opportunities and challenges. Recent years have seen the emergence of attention to ethical, legal and social issues (ELSI) in the field of Information and Communication Technology. However, disclosing (and addressing) ELSI issues in design is still a challenge because they are inherently relational, arising from interactions between people, the material and design of the artifact, and the context. In this article, we discuss approaches for addressing such ‘deeper’ and ‘wider’ political implications, values and ethical, legal and social implications that arise between practices, people and technology. Based on a case study from the BRIDGE project, which has provided the opportunity for deep engagement with these issues through the concrete exploration and experimentation with technologically augmented practices of emergency response, we present insights from our interdisciplinary work aiming to make design and innovation projects ELSI-aware. Crucially, we have seen in our study a need for a shift from privacy by design towards designing for privacy, collaboration, trust, accessibility, ownership, transparency etc., acknowledging that these are emergent practices that we cannot control by design, but rather that we can help to design for—calling for approaches that allow to make ELSI issues explicit and addressable in design-time.     

On communication models for algorithm design in networked sensor systems: A case study

Towards building a systematic methodology of algorithm design for applications of networked sensor systems, we formally define two link-wise communication models, the Collision Free Model (CFM) and the Collision Aware Model (CAM). While CFM provides ease of programming and analysis for high level application functionality, CAM enables more accurate performance analysis and hence more efficient algorithms through cross-layer optimization, at the expense of increased programming and analysis complexity. These communication models are part of an abstract network model, above which algorithm design and performance optimization is performed. We use the example of optimizing a probability based broadcasting scheme under CAM to illustrate algorithm optimization based on the defined models. Specifically, we present an analytical framework that facilitates an accurate modeling and analysis for the probability based broadcasting in CAM (PB_CAM). Our analytical results indicate that (1) the optimal broadcast probability for either maximizing the reachability within a given latency constraint or minimizing the latency for a given reachability constraint decreases rapidly with node density, and (2) the optimal probability for either maximizing the reachability with a given energy constraint or minimizing the energy cost for a given reachability constraint varies slowly between 0 and 0.1 over the entire range of the variations in node density. Our analysis is also confirmed by extensive simulation results.     

Playful public participation in urban planning: A case study for online serious games

The aim of this paper is to study the implementation of online games to encourage public participation in urban planning. Its theoretical foundations are based on previous work in public participatory geographical information systems (PP GISs), play and games, with a special focus on serious games. Serious games aim to support learning processes in a new, more playful way. We developed the concept of playful public participation in urban planning, including playful elements such as storytelling, walking and moving, sketching, drawing, and games. A group of students designed an online serious public participatory game entitled NextCampus. The case study used in NextCampus was taken from the real-world question of a possible move of a university campus to a new location in the city of Hamburg, Germany. The development of the serious public participatory game NextCampus resulted in a physical prototype, user interface design, and a computational model of the game. The NextCampus game was tested with the help of two groups of urban planning students and presented to three external experts who provided valuable recommendations for further development. The critical comments questioned the level of complexity involved in such games. The positive comments included recognition of the potential for joy and the playfulness a game like NextCampus could evoke.     

Integrated BIM,game engine and VR technologies for healthcare design: A case study in cancer hospital

The results of healthcare design should meet the requirements of design teams as well as healthcare stakeholders. However, misunderstandings that occur between the design teams and healthcare stakeholders when using 2D illustrations leads to the need for re-design and rework during the design phase. To overcome this problem, this study develops a Database-supported VR/BIM-based Communication and Simulation (DVBCS) system integrated with BIM, game engine and VR technologies for healthcare design special in the Semi-immersed VR environment. The DVBCS system is applied in a case study of a design project of a cancer center in Taiwan to verify the system and demonstrate its effectiveness in practice. The results demonstrate that a DVBCS system is an effective visual communication and simulation platform for healthcare design. The advantage of the DVBCS system lies not only in improving the communication efficiency between the design teams and healthcare stakeholders, but also in facilitating visual interactions and easing the decision-making process while communicating in the 3D VR/BIM environment. The effective use of the proposed DVBCS system will assist design teams and stakeholders significantly in systematically handling healthcare design work in future healthcare design.     

Exploring interactive style and user experience design for social web of things of Chinese users: A case study in Beijing

This study designed an interactive IoT (Internet of Things) service on mobile devices based upon the concept of Social Web of Things (SWoT), with which users can interact with IoT in the same way they use the social network services. In order to integrate IoT into Chinese daily use, this study also investigated how Chinese users interact with things and IoT technologies. A four-phase study among users living in Beijing was conducted with a lifecycle of user-centered design. Results revealed that SWoT could activate users׳ intuitive understanding of social network services, and make the interaction with SWoT natural in their own ways. Users living in Beijing tended to be utility-oriented and highly emphasized efficiency; they were distinctive in uncertainty avoidance and preference of hierarchical way of managing things. Our results suggested implications for the design of user-centered IoT systems in China, and shed light on improvements for the performance of IoT systems and balance of requirements between users and system design.