Modelling with stakeholders to integrate biodiversity into land-use planning – Lessons learned in Réunion Island (Western Indian Ocean)

This paper considers participatory modelling to integrate biodiversity conservation into land use planning and to facilitate the incorporation of ecological knowledge into public decision making for spatial planning. Réunion Island has experienced rapid urban and agricultural expansion, which threaten its unique biodiversity. In this context, we designed three participatory modelling sequences, involving overall 24 multidisciplinary researchers and stakeholders. The sequences aimed: (1) to map land-use and biodiversity, (2) to develop a conservation plan following systematic conservation planning principles using a spatial optimization tool (MARXAN) and (3) to simulate coupled land-use/conservation scenarios using a multi-agent system (MAS). The conservation plan confirms that priority areas for biodiversity protection are located on the coast where rapid land-use changes occur. Nevertheless, stakeholders from the urban and agricultural sector did not participate to this sequence. Indeed, conservation planning tools are useful to locate conservation priorities but they have to be designed with stakeholders to be accepted as negotiation tool. Besides, the researchers engaged in this second sequence were perceived as conservation stakeholders rather than holders of scientific knowledge. In the third sequence, the researchers involved adopted the stance of facilitating the elicitation of each stake and gathered trust from stakeholders. Overall, we conclude that the participatory development of land-use simulation models should be promoted to explore alternative scenarios for biodiversity conservation with stakeholders. In a situation of land-use conflict, a gradual and sequential participatory modelling approach should be implemented to fit into public decision-making processes.     

Modeling and Visualization for a Production Planning Decision Support System

This paper describes the process of decision support systems development for the optimization of the aggregate production planning problem for an important manufacturer of applicances in Chile. This work is part of a more general research effort, whose purpose is to build a generator of software applications for logistic problems in industry, based on optimization models. We take advantage of powerful tools and approaches for the modeling stage, and for building systems with user friendly interfaces and good data management capabilities. The production planning problem is formulated as a mixed integer programming model, which is solved using CPLEX. The system is currently being used by the company for their decision processes in manufacturing.     

炼钢连铸作业计划的混合遗传优化与仿真分析

为提高炼钢连铸作业计划制定的效率和质量,面向生产工艺流程网络图,建立了一种基于遗传算法与蚁群算法相结合的混合智能优化方法,进行炼钢连铸生产作业计划的编制,并可实现常见扰动情况下的重计划制定;利用基于元胞自动机思想建立的炼钢连铸流程仿真模型,进行生产作业计划的仿真分析和评价。将计划编制模型与仿真模型有机结合,为作业计划的在线动态评价和自动调整提供了一种有效手段。针对某钢厂的仿真实验研究表明：提出的智能优化方法能较好地解决炼钢-连铸生产作业计划的时间不确定性优化问题,可快速生成炉次间作业无冲突的优化生产作业计划。     

Relevancy and role of whole-farm models in supporting smallholder farmers in planning their agricultural season

The way a model is designed to assist farmers in their decision-making may influence how it is understood and perceived by farmers and shape interactions between farmers and model users (researcher, advisor). This study compared the strengths and weaknesses of three types of whole farm models used by researchers to assist 18 crop-livestock farmers in Burkina Faso in planning the next agricultural season. Due to its simplicity, the static simulation tool of annual farm stocks and flows led to superior changes in the farmers' knowledge and practices. The rule-based dynamic simulation tool helped the researchers grasp farmers' decision-making processes but was difficult for farmers to understand due to the discrepancy between its multi-annual time step and the farmers' short-term planning horizon. The optimisation tool stimulated more strategic discussions regarding paths to improve farm income despite a design that was distant from the farmers' reality.     

数控加工中路径规划与速度插补综述

数控技术在现代制造工业中被广泛使用,相关研究一直为学界和业界共同关注。数控技术的传 统流程主要包含刀具路径规划和进给速度插补。为实现高速高精加工,人们通常将路径规划与速度插补中的若 干问题转换成数理优化模型,针对工程应用问题的复杂性,采用分步迭代优化的思路进行求解,但所得的结果 往往只是局部最优解。其次,路径规划与速度插补都是为了加工一个工件曲面,分两步进行处理虽然简化了计 算,但也导致不能进行整体优化。因此,为了更好地开展路径规划与速度插补一体化设计与全局最优求解的研 究,系统性地了解并学习已有的代表性工作是十分有必要的。所以将逐次介绍数控加工中刀具路径规划与速度 插补的相关方法与技术进展,包括基于端铣的加工路径规划;刀轴方向优化;G 代码加工以及拐角过渡;参数 曲线路径的进给速度规划等国内外相关研究以及最新提出的一些新型加工优化方法。     

A spreadsheet-based decision support tool for blending problems in brass casting industry

This paper has discussed development and implementation of spreadsheet-based decision support tools for modeling and solving blending problems in a large-scale brass factory in Turkey. The user interfaces have been designed in Microsoft Excel which is linked with Lingo modeling language and optimizer. One decision support tool was developed from a single-blend LP model and has been in use at the foundry; it is run several times a day by foremen to obtain optimal raw material quantities for melting operations. That the users were foremen without any engineering and optimization background posed a serious challenge to produce a decision support tool that is easily applicable at the foundry, for which spreadsheet interfaces have produced an effective solution. The paper has elaborated on difficulties faced in the development and implementation and their solutions as well as design of the interface. A similar tool has also been developed for master production planning, which has not been put to use yet. Issues have been discussed regarding its integration into the production planning system and its relationship with the single-blend tool.     

Optimal selection and placement of BMPs and LID practices with a rainfall-runoff model

A decision support tool, which links a hydrologic/water quality model (L-THIA-LID 2.1) with optimization algorithms (AMALGAM) using a computational efficiency framework (MLSOPT), was developed to optimally implement BMPs and LID practices to reduce runoff and pollutant loads. The decision support tool was applied in the Crooked Creek watershed, Indiana, USA. For initial expenditures on practices, the environmental benefits increased rapidly as expenditures increased. However, beyond certain expenditure levels, additional spending did not result in noticeable additional environmental impacts. Compared to random placement of practices, the optimization strategy provided 3.9–7.7 times the level of runoff/pollutant load reductions for the same expenditures. To obtain the same environmental benefits, costs of random practices placement were 4.2–14.5 times the optimized practice placement cost. The decision support tool is capable of supporting decision makers in optimally selecting and placing BMPs and LID practices to obtain maximum environmental benefits with minimum costs.     

基于仿真和蚁群算法的公交动态交通规划研究

针对越来越复杂的道路交通系统,研究其中的动态交通规划问题。以达到对交通进行合理规划的目的。采用计算机仿真技术构建动态交通规划模型,应用蚁群算法解决基于仿真的动态交通规划优化问题。在所建模型的基础上,通过蚁群算法进行求解。实验结果令人满意。仿真方法可以将普通动态交通规划模型无法反映的随机因素考虑在内,使得动态交通规划的结果更加具有现实中的指导意义。将优化技术嵌入到仿真过程中。在仿真环境下使输出响应不断地得到改进,从而实现道路交通系统性能的优化。数据实例表明,该方法是正确的、可行的、有效的,可以为实际的道路交通规划提供有力地决策支持。     

Integrated Structural–Architectural Design for Interactive Planning

Traditionally, building floor plans are designed by architects with their usability, functionality and architectural aesthetics in mind; however, the structural properties of the distribution of load‐bearing walls and columns are usually not taken into account at this stage. In this paper, we propose a novel approach for the design of architectural floor plans by integrating structural layout analysis directly into the planning process. In order to achieve this, we introduce a planning tool which interactively enforces checks for structural stability of the current design, and which on demand proposes how to stabilize it if necessary. Technically, our solution contains an interactive architectural modelling framework as well as a constrained optimization module where both are based on respective architectural rules. Using our tool, an architect can predict already in a very early planning stage whose designs are structurally sound such that later changes due to stability reasons can be prevented. We compare manually computed solutions with optimal results of our proposed automated design process in order to show how much our proposed system can help architects to improve the process of laying out structural models optimally.     

Closing the gap between planning and control: A multiscale MPC cascade approach

A one-to-many, multiscale model predictive control (MPC) cascade is proposed for closing the gap between production planning and process control. The gap originates from the fact that planning and control use models at different scales, and the gap has existed since the first planning tool was deployed. Multiscaleness has been at the core of the challenge to coordinating heterogeneous solution layers, and there has been a lack of systematic treatment for multiscaleness in a control system. The proposed MPC cascade is devised as a plantwide master MPC controller cascading on top of multiple (n) slave MPC controllers.¹ The master can use a coarse-scale, single-period planning model as the gain matrix of its dynamic model, and it then can control the same set of variables that are only monitored by the planning tool. Each slave controller, using a fine-scale model, performs two functions: (1) model predictive control for a process unit, and (2) computation of proxy limits that represent the current constraints inside the slave. The master's economic optimizer amends the single-period planning optimization in real time with the slave's proxy limits, and the embedded planning model is thus reconciled with the MPC models for process units in the sense that the master's optimal solution now honors the slave's constraints. With this new approach, the proposed MPC cascade becomes the plantwide closed-loop control system that performs the reconciled planning optimization in its master controller and carries out the just-in-time production plan through its slave controllers.     

基于OPNET的网络压力仿真

针对网络规划和优化过程中压力测试工具使用的不足,提出基于OPNET的网络压力仿真方法,建立包含不同网络负载的多个仿真场景,以对FFP服务的压力仿真为例,收集并对比这些场景中服务器和网络的吞吐量、时延及丢包率,分析各种网络运行数据,得出网络负载情况。结果表明,利用OPNET软件可以有效地进行网络压力仿真。     

Process planning optimization for parallel drilling of blind holes using a two phase genetic algorithm

Determining the optimal process parameters and machining sequence is essential in machining process planning since they significantly affect the cost, productivity, and quality of machining operations. Process planning optimization has been widely investigated in single-tool machining operations. However, for the research reported in process planning optimization of machining operations using multiple tools simultaneously, the literature is scarce. In this paper, a novel two phase genetic algorithm (GA) is proposed to optimize, in terms of minimum completion time, the process parameters and machining sequence for two-tool parallel drilling operations with multiple blind holes distributed in a pair of parallel faces and in multiple pairs of parallel faces. In the first phase, a GA is used to determine the process parameters (i.e., drill feed and spindle speed) and machining time for each hole subject to feed, spindle speed, thrust force, torque, power, and tool life constraints. The minimum machining time is the optimization criterion. In the second phase, the GA is used to determine the machining sequence subject to hole position constraints (i.e., the distribution of the hole locations on each face is fixed). The minimum operation completion time is the optimization criterion in this phase. Simulation results are presented to demonstrate the effectiveness of the proposed algorithm in solving the process planning optimization problem for parallel drilling of blind holes on multiple parallel faces. In order to evaluate the performance of proposed algorithm, the simulation results are compared to a methodology that utilizes the exhaustive method in the first phase and a sorting algorithm.     

Supply network modelling and simulation methodology

Supply network management in today’s business climate characterized by high uncertainty, globalization of business, outsourcing, shorter product life-cycles, and high customer expectations is extremely challenging. Simulation can be a valuable tool for supply network analysis, planning, optimization, evaluation, and risk management. This paper presents a methodology for modelling both structure and dynamics of complex supply networks based on process approach. It also describes the model-driven simulation methodology and the main components of the simulation software solution: model database, process library, knowledge base, and execution engine. Finally, simulation results of the case supply network are presented.     

Simulation of a storm sewer network in industrial area: Comparison between models calibrated through experimental data

The purpose of this article is to test the performance of two commercial models for the simulation of sewer systems (InfoWorks, developed by Wallingford Ltd and Mouse, developed by DHI), basing on the experimental data sampled in a 1.15 ha watershed located near Bologna, Italy. The experimental catchment is part of a truck transit and parking area, completely asphalt paved and drained into a first flush tank. Hydrologic and water quality data collected for almost 8 months inside the tank have been used to calibrate the models through a trial and error procedure for both quantity and quality aspects. A sensitivity analysis for the most relevant quality–quantity parameters has also been performed, testing therefore the behaviour of these models in a small impervious watershed and their reliability as a support tool in the design phase.     

One MEMS design tool with maximal six design flows

This paper presents one MEMS design tool with a total six of design flows, which makes it possible that the MEMS designers choose the most suitable design flow for their specific devices. The design tool is divided into three levels and interconnected by six interfaces. The three levels are the lumped-element model based system level, finite element analysis based device level and process level, which cover nearly all modeling and simulation functions for MEMS design. The six interfaces are proposed to automatically transmit the design data between every two levels, thus the maximal six design flows could be realized. The interfaces take the netlist, solid model and layout as the data inlet and outlet for the system, device and process level respectively. The realization of these interfaces are presented and verified by design examples, which also proves that enough flexibility in the design flow can really increase the design efficiency.     

A quantitative phosphorus loss assessment tool for agricultural fields

In the United States, government sponsored conservation programs are under increasing pressure to quantify the environmental benefits of practices they subsidize. To meet this objective, conservation planners need tools to accurately predict phosphorus (P) loss from agricultural lands. Existing P export coefficient based tools are easy to use, but do not adequately account for local conditions. Hydrologic and water quality models are more accurate, but are prohibitively complex for conservation planners to use. Pasture Phosphorus Management (PPM) Plus was developed as a user-friendly P and sediment loss prediction tool based on the Soil and Water Assessment Tool (SWAT), a popular comprehensive hydrologic and water quality model. PPM Plus is applicable under a wide variety of management options and conservation practices and simple enough for use by conservation planners. SWAT hydrologic components were calibrated to allow application anywhere in the State of Oklahoma. The SWAT model was modified to include soil P algorithm updates and improved representation of conservation practices. This tool was successfully validated using 286 field years of measured data from the southern United States. PPM Plus allows the development of more effective conservation plans by allowing planners to evaluate pollutant losses resulting from a particular management strategy prior to implementation.     

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.     

Modeling and optimization of manufacturing process performance using Modelica graphical representation and process analytics formalism

This paper concerns the development of a design methodology and its demonstration through a prototype system for performance modeling and optimization of manufacturing processes. The design methodology uses a Modelica simulation tool serving as the graphical user interface for manufacturing domain users such as process engineers to formulate their problems. The Process Analytics Formalism, developed at the National Institute of Standards and Technology, serves as a bridge between the Modelica classes and a commercial optimization solver. The prototype system includes (1) manufacturing model components’ libraries created by using Modelica and the Process Analytics Formalism, and (2) a translator of the Modelica classes to Process Analytics Formalism, which are then compiled to mathematical programming models and solved using an optimization solver. This paper provides an experiment toward the goal of enabling manufacturing users to intuitively formulate process performance models, solve problems using optimization-based methods, and automatically get actionable recommendations.     

Multi-objective model auto-calibration and reduced parameterization: Exploiting gradient-based optimization tool for a hydrologic model

Multi-objective model optimization methods have been extensively studied based on evolutionary algorithms, but less on gradient-based algorithms. This study demonstrates a framework for multi-objective model calibration/optimization using gradient-based optimization tools. Model-independent software Parameter ESTimation (PEST) was used to auto-calibrate ISWAT, a modified version of the distributed hydrologic model Soil and Water Assessment Tool (SWAT2005), in the Shenandoah River watershed. The time-series processor TSPROC was used to combine multiple objectives into the auto-calibration process. Two sets of roughness coefficients for main channels, one assigned and calibrated according on soil types and one determined via empirical equations, were examined for stream discharge simulation. Five different weighting alternatives were investigated for their effects on ISWAT calibrations. Results showed that using Manning's roughness coefficients obtained from empirical equations improves simulation results and calibration efficiency. Applying a two-step weighting alternative to different observation groups would provide the best calibration results.