The automatic layout model in the sequencing of construction activities of multi-objective diaphragm wall unit by using self-learning neural network

Foundation construction process has been an important key point in a successful construction engineering. The frequency of using diaphragm wall construction method among many deep excavation construction methods in Taiwan is the highest in the world. The traditional view of managing diaphragm wall unit in the sequencing of construction activities is to establish each phase of the sequencing of construction activities by heuristics. However, it conflicts final phase of engineering construction with unit construction and effects planning construction time. In order to avoid this kind of situation, we use management of science in the study of diaphragm wall unit construction to formulate multi-objective combinational optimization problem. Because the characteristic (belong to NP-Complete problem) of problem mathematic model is multi-objective and combining explosive, it is advised that using the 2-type Self-Learning Neural Network (SLNN) to solve the N=12, 24, 36 of diaphragm wall unit in the sequencing of construction activities program problem. In order to compare the liability of the results, this study will use random researching method in comparison with the SLNN. It is found that the testing result of SLNN is superior to random researching method in whether solution-quality or Solving-efficiency.

Engaging in European spatial planning: a central and Eastern European perspective on the territorial cohesion debate

The following paper sets out to determine the differential extent of the engagement of Central and Eastern European (CEE) member states with the European spatial planning (ESP) debate over territorial cohesion. It focuses on the written statements submitted in response to the European Commission “Green Paper on Territorial Cohesion” consultation in 2009. The geographical distribution of the respondents is analysed, before CEE member states’ responses are examined in detail, to explore the diverse interpretations of the concept of “territorial cohesion” among CEE actors. While the data collection for this paper has been restricted empirically to the consultation process, it reflects its findings in consideration of member states’ engagement with the debate as it manifested before and after the Green Paper. The debate over the exact conceptual and operational “framing” of territorial cohesion, launched by the European Commission's Green Paper, constitutes one of the many arenas through which ESP currently evolves, together with the transnational initiatives developed in the framework of the European Territorial Cooperation objective, the European Observation Network for Territorial Development and Cohesion (ESPON) and the process that recently led to the publication of the Territorial Agenda of the European Union 2020. The paper concludes that the overall level of engagement of CEE actors in ESP is proportionally lower in comparison with that of their northwestern European counterparts. The increasing involvement of some CEE member states within the ESPON 2013 Programme, as well as the activities undertaken by the Hungarian and Polish EU Presidencies in 2011, suggests that this level of CEE engagement is growing albeit differentially.

Multi-level planning for semi-autonomous vehicles in traffic scenarios based on separation maximization

The planning of semi-autonomous vehicles in traffic scenarios is a relatively new problem that contributes towards the goal of making road travel by vehicles free of human drivers. An algorithm needs to ensure optimal real time planning of multiple vehicles (moving in either direction along a road), in the presence of a complex obstacle network. Unlike other approaches, here we assume that speed lanes are not present and that different lanes do not need to be maintained for inbound and outbound traffic. Our basic hypothesis is to carry forward the planning task to ensure that a sufficient distance is maintained by each vehicle from all other vehicles, obstacles and road boundaries. We present here a 4-layer planning algorithm that consists of road selection (for selecting the individual roads of traversal to reach the goal), pathway selection (a strategy to avoid and/or overtake obstacles, road diversions and other blockages), pathway distribution (to select the position of a vehicle at every instance of time in a pathway), and trajectory generation (for generating a curve, smooth enough, to allow for the maximum possible speed). Cooperation between vehicles is handled separately at the different levels, the aim being to maximize the separation between vehicles. Simulated results exhibit behaviours of smooth, efficient and safe driving of vehicles in multiple scenarios; along with typical vehicle behaviours including following and overtaking.

A peak reduction scheduling algorithm for storage devices on the low voltage network

Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.

Re-evaluating the place of urban planning history

This commentary seeks to prompt new discussion about the place of urban planning history in the era of contemporary globalisation. Given the deep historic engagement of urban planning thought and practice with ‘place’ shaping and thus with the constitution of society, culture and politics, we ask how relevant is planning's legacy to the shaping of present day cities. Late twentieth century urban sociology, cultural and economic geography have demonstrated the increasing significance of intercity relations and the functional porosity of metropolitan boundaries in the network society, however statutory urban planning systems remain tied to the administrative geographies of states. This ‘territorial fixing’ of practice constrains the operational space of planning and, we argue, also limits its vision to geopolitical scales and agendas that have receding relevance for emerging urban relations. We propose that a re-evaluation of planning history could have an important part to play in addressing this spatial conundrum.

The diffusion of the Transition Network in four European countries

The Transition Network exemplifies the potential of social movements to create spaces of possibility for alternatives to emerge in the interstices of mainstream, neoliberal economies. Yet, little work has been carried out so far on the Transition Network or other grassroots innovations for sustainability in a way that reveals their actual patterns of diffusion. This graphic of the diffusion of the Transition Network visualises its spatial structure and compare diffusion patterns across Italy, France, Great Britain and Germany. The graphics show that the number of transition initiatives in the four countries has steadily increased over the past eight years, but the rate of increase has slowed down in all countries. The maps clearly show that in all four countries the diffusion of the Transition Network has not been spatially even. The graphic suggests that in each country transition initiatives are more likely to emerge in some geographical areas (hotspots) than in others (cold spots). While the existence of a spatial structure of the Transition Network may result from the combination of place-specific factors and diffusion mechanisms, these graphics illustrate the importance of better comprehending where grassroots innovations emerge.

Using GIS Network Analyst to Identify Suppliers for a Produce Co-op in Waterville, ME

The idea for organizing a cooperative market on Waterville Main Street was proposed by Aime Schwartz in the fall of 2008. The Co-op would entail an open market located on Main Street to provide fresh, local produce and crafts to town locals. Through shorter delivery distances and agreements with local farmers, the co-op theoretically will offer consumers lower prices on produce than can be found in conventional grocery stores, as well as an opportunity to support local agriculture. One of the tasks involved with organizing the Co-op is to source all of the produce from among the hundreds of farmers located in Maine. The purpose of this project is to show how Geographic Information System (GIS) tools can be used to help the Co-op and other businesses a) site nearby farms that carry desired produce and products, and b) determine which farms are closest to the business site. Using GIS for this purpose will make it easier and more efficient to source produce suppliers, and reduce the workload on business planners. GIS Network Analyst is a tool that provides network-based spatial analysis, and can be used in conjunction with traditional GIS technologies to determine not only the geometric distance between points, but also distance over existing networks (like roads). We used Network Analyst to find the closest produce suppliers to the Co-op for specific produce items, and compute how far they are over existing roads. This will enable business planners to source potential suppliers by distance before contacting individual farmers, allowing for more efficient use of their time and a faster planning process.

Multi-Objective Pipe Smoothing Genetic Algorithm For Water Distribution Network Design

This paper describes the formulation of a Multi-objective Pipe Smoothing Genetic Algorithm (MOPSGA) and its application to the least cost water distribution network design problem. Evolutionary Algorithms have been widely utilised for the optimisation of both theoretical and real-world non-linear optimisation problems, including water system design and maintenance problems. In this work we present a pipe smoothing based approach to the creation and mutation of chromosomes which utilises engineering expertise with the view to increasing the performance of the algorithm whilst promoting engineering feasibility within the population of solutions. MOPSGA is based upon the standard Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and incorporates a modified population initialiser and mutation operator which directly targets elements of a network with the aim to increase network smoothness (in terms of progression from one diameter to the next) using network element awareness and an elementary heuristic. The pipe smoothing heuristic used in this algorithm is based upon a fundamental principle employed by water system engineers when designing water distribution pipe networks where the diameter of any pipe is never greater than the sum of the diameters of the pipes directly upstream resulting in the transition from large to small diameters from source to the extremities of the network. MOPSGA is assessed on a number of water distribution network benchmarks from the literature including some real-world based, large scale systems. The performance of MOPSGA is directly compared to that of NSGA-II with regard to solution quality, engineering feasibility (network smoothness) and computational efficiency. MOPSGA is shown to promote both engineering and hydraulic feasibility whilst attaining good infrastructure costs compared to NSGA-II.

Reuse-based test planning for core-based systems-on-chip

Electronic applications are currently developed under the reuse-based paradigm. This design methodology presents several advantages for the reduction of the design complexity, but brings new challenges for the test of the final circuit. The access to embedded cores, the integration of several test methods, and the optimization of the several cost factors are just a few of the several problems that need to be tackled during test planning. Within this context, this thesis proposes two test planning approaches that aim at reducing the test costs of a core-based system by means of hardware reuse and integration of the test planning into the design flow. The first approach considers systems whose cores are connected directly or through a functional bus. The test planning method consists of a comprehensive model that includes the definition of a multi-mode access mechanism inside the chip and a search algorithm for the exploration of the design space. The access mechanism model considers the reuse of functional connections as well as partial test buses, cores transparency, and other bypass modes. The test schedule is defined in conjunction with the access mechanism so that good trade-offs among the costs of pins, area, and test time can be sought. Furthermore, system power constraints are also considered. This expansion of concerns makes it possible an efficient, yet fine-grained search, in the huge design space of a reuse-based environment. Experimental results clearly show the variety of trade-offs that can be explored using the proposed model, and its effectiveness on optimizing the system test plan. Networks-on-chip are likely to become the main communication platform of systemson- chip. Thus, the second approach presented in this work proposes the reuse of the on-chip network for the test of the cores embedded into the systems that use this communication platform. A power-aware test scheduling algorithm aiming at exploiting the network characteristics to minimize the system test time is presented. The reuse strategy is evaluated considering a number of system configurations, such as different positions of the cores in the network, power consumption constraints and number of interfaces with the tester. Experimental results show that the parallelization capability of the network can be exploited to reduce the system test time, whereas area and pin overhead are strongly minimized. In this manuscript, the main problems of the test of core-based systems are firstly identified and the current solutions are discussed. The problems being tackled by this thesis are then listed and the test planning approaches are detailed. Both test planning techniques are validated for the recently released ITC’02 SoC Test Benchmarks, and further compared to other test planning methods of the literature. This comparison confirms the efficiency of the proposed methods.

Interior point algorithm for linear programming used in transmission network synthesis

This article presents a well-known interior point method (IPM) used to solve problems of linear programming that appear as sub-problems in the solution of the long-term transmission network expansion planning problem. The linear programming problem appears when the transportation model is used, and when there is the intention to solve the planning problem using a constructive heuristic algorithm (CHA), ora branch-and-bound algorithm. This paper shows the application of the IPM in a CHA. A good performance of the IPM was obtained, and then it can be used as tool inside algorithm, used to solve the planning problem. Illustrative tests are shown, using electrical systems known in the specialized literature. (C) 2005 Elsevier B.V. All rights reserved.

Transmission system expansion planning by an extended genetic algorithm

The paper presents an extended genetic algorithm for solving the optimal transmission network expansion planning problem. Two main improvements have been introduced in the genetic algorithm: (a) initial population obtained by conventional optimisation based methods; (b) mutation approach inspired in the simulated annealing technique, the proposed method is general in the sense that it does not assume any particular property of the problem being solved, such as linearity or convexity. Excellent performance is reported in the test results section of the paper for a difficult large-scale real-life problem: a substantial reduction in investment costs has been obtained with regard to previous solutions obtained via conventional optimisation methods and simulated annealing algorithms; statistical comparison procedures have been employed in benchmarking different versions of the genetic algorithm and simulated annealing methods.

Multistage and coordinated planning of the expansion of transmission systems

In this paper, an efficient genetic algorithm (GA) is presented to solve the problem of multistage and coordinated transmission expansion planning. This is a mixed integer nonlinear programming problem, difficult for systems of medium and large size and high complexity. The GA presented has a set of specialized genetic operators and an efficient form of generation of the initial population that finds high quality suboptimal topologies for large size and high complexity systems. In these systems, multistage and coordinated planning present a lower investment than static planning. Tests results are shown in one medium complexity system and one large size high complexity system.