基于多准则遗传算法的航线规划

飞行航线规划是中小型飞机执行长途飞行任务时的重要工作。通过建立问题的多准则最短路径问题模型,提出一种多准则最短路径遗传算法求解优化飞行航线。通过理论分析证明了算法的收敛性。仿真实验验证了该算法的有效性。     

Integrating environmental objectives in the operational planning ofprinted circuit board assembly

This paper presents a methodology for operational control of printed circuit board (PCB) assembly systems with respect to environmental objectives for managing per-unit and per-setup waste flows. The approach builds upon the concept of unit process modeling, process chaining and evaluation of multicriteria effects first applied to product design. Three approaches are used to guide planning and control decisions for the management of hazard profiles at the facility level: product assignment, worker assignment, and a hybrid approach. The optimization models seek to balance overall waste mass and facility-level hazard given throughput constraints and demand requirements. A case example is given for scheduling six board types over four production lines in a two-shift operation     

Incorporating component reuse, remanufacture, and recycle into product portfolio design

Product take-back laws have been enacted in the Netherlands, and the European Commission is expected to follow suit. The legislation mandates that manufacturers bear the economic burden of collection and disposal of products at the end of their useful lives. Reuse or remanufacturing of some components might be more cost-effective than disposal and provide an opportunity for recovery of their economic value. However, manufacturers have not traditionally engaged in the long-range planning over several product lifecycles that cost-effective reuse or remanufacturing requires. This paper develops a model for incorporating long-range planning for component reuse in product design. The model employs a product portfolio approach based on market segmentation, rather than a single product. The model is embedded in a decision tool that aids in determining when a product should be taken back, and which components should be reused, recycled, or disposed. A case study of a line of personal computers (PCs) demonstrates an implementation of the model. It also shows that if product take-back is mandated, it is in the PC manufacturer's best interest to shift from selling a product to essentially selling a service by controlling when the product is taken back and, thus, effectively creating a leasing program. The portfolio approach creates opportunities for the design engineer to distribute the cost, reliability, and environmental impacts of component reuse, remanufacture, and recycling in such a way that the end result is higher customer satisfaction than designing one product for all customer groups.     

Macro pipelining based scheduling on high performance heterogeneousmultiprocessor systems

Presents a technique for pipelining heterogeneous multiprocessor systems, macro pipelining based scheduling. The problem can be identified as a combination of optimal task/processor assignment to pipeline stages as well as a scheduling problem. The authors propose a new technique based on iterative applications of partitioning and scheduling schemes whereby the number of pipeline stages are identified and the scheduling problem is solved. The pipeline cycle is optimized in two steps. The first step finds a global coarse solution using the ratio cut partitioning technique. This is subsequently improved by the iterative architecture driven partitioning and the repartitioning and time axis relabeling techniques of the second step. The authors have considered a linear interprocessor communication cost model in scheduling. The proposed technique is applied to several examples. They find that for these examples, the proposed macro pipelining based scheduling can improve the throughput rate several times that of the conventional homogeneous multiprocessor scheduling algorithms     

A methodology for product mix planning in semiconductor foundrymanufacturing

Since a semiconductor foundry plant manufactures a wide range of memory and logic products using the make-to-order business model, the product mix is an important production decision. This paper first describes the characteristics of the product mix planning problem in foundry manufacturing that are attributable to the long flow time and queuing network behaviors. The issues of time bucket selection, mix optimization and bottleneck-based planning are next addressed. A decision software system based on integer linear programming techniques and a heuristic procedure has been implemented for mix planning. Data provided by a wafer plant has been used to study problems related to product mix planning. It was determined that the suitable time bucket of planning is either one week or one month and the lead-time offset factor should be included in the logic of workload calculation. This paper also presents various facets of product mix decisions and how they should be integrated with operations management     

Analytical computation of the energy-efficient optimal planning in rest-to-rest motion of constant inertia systems

Among the techniques to improve energy efficiency of mechatronic systems, the synthesis of optimized motion profiles has been proved to be an effective and almost costless method. In order to boost the use of this approach, this paper proposes an analytical method for improving energy efficiency in rest-to-rest motion through optimal planning, by selecting both the optimal motion law and the optimal motion time (duration). The proposed technique is suitable for constant inertia systems. As a matter of fact, this kind of mechatronic systems covers a wide range of applications in production, packaging or logistic plants.The method practical application is straightforward, since it just relies on the knowledge of the task specifications and of some system parameters to compute the optimal motion time for each selected trajectory and to compare analytically different motion profiles. The limitations due the servo-actuator (torque, speed, bandwidth), to machine throughput requirements, as well as the smoothness specifications (acceleration and jerk limitations, degree of continuity) are explicitly accounted for through bounds, to ensure the feasibility of the motion profiles developed.Since the proposed method proposes an analytical algebraic equation, it does not require either time-consuming simulations and trial-and-error evaluations, or numerical optimizations. Hence, it is well suited for industrial mechatronic applications.     

Technology portfolio management: optimizing interdependent projectsover multiple time periods

In order to maintain competitiveness, companies need to continually invest in technology projects. However, resource limitations require an organization to strategically allocate resources to a subset of possible projects. A variety of tools and methods can be used to select the optimal set of technology projects. However, these methods are only applicable when projects are independent and are evaluated in a common funding cycle. When projects are interdependent, the complexity of optimizing even a moderate number of projects over a small number of objectives and constraints can become overwhelming. This paper presents a model developed for the Boeing Company, Seattle, WA, USA, to optimize a portfolio of product development improvement projects. Using a dependency matrix, which quantifies the interdependencies between projects, a nonlinear, integer program model was developed to optimize project selection. The model also balances risk, overall objectives and the cost and benefit of the entire portfolio. Once the optimum strategy is identified, the model enables the team to quickly quantify and evaluate small changes to the portfolio     

Synthesis and Time Partitioning for Reconfigurable Systems

This paper aims to introduce a time partitioning algorithm which is an important step during the design process for fully reconfigurable systems. This algorithm is used to solve the time partitioning problem. It divides the input task graph model to an optimal number of partitions and puts each task in the appropriate partition so that the latency of the input task graph is optimal. Also a part of this paper is consecrated for implementation of some examples on a fully reconfigurable architecture following our approach.     

Optimal preventive maintenance scheduling in semiconductor manufacturing

Preventive maintenance (PM) scheduling is a very challenging task in semiconductor manufacturing due to the complexity of highly integrated fab tools and systems, the interdependence between PM tasks, and the balancing of work-in-process (WIP) with demand/throughput requirements. In this paper, we propose a two-level hierarchical modeling framework. At the higher level is a model for long-term planning, and at the lower level is a model for short-term PM scheduling. Solving the lower level problem is the focus of this paper. We develop mixed-integer programming (MIP) models for scheduling all due PM tasks for a group of tools, over a planning horizon. Interdependence among different PM tasks, production planning data such as projected WIP levels, manpower constraints, and associated PM time windows and costs, are incorporated in the model. Results of a simulation study comparing the performance of the model-based PM schedule with that of a baseline reference schedule are also presented.     

Strategic telecommunications networks planning in the context ofemerging technologies, architectures, and services

A methodology is presented for conducting strategic network planning studies under a new set of planning assumptions. The key element of the described methodology is a mathematical model of the equipment-replacement decision-making process that explicitly captures the economic impact of emerging technologies, architectures, and services. The general replacement decision model (GRDM) is a mathematical model that computes the optimal sequence of replacement times for particular pieces of telecommunications network equipment. GRDM takes information about costs and revenues and their trends in time associated with existing and emerging technologies and services and calculates the sequence of technology replacement intervals that minimizes the net present worth of expenditures associated with embedded plant and its replacements. The generality of the model supports its application to a broad range of network evolution issues, including the deployment of fiber optics and intelligent network features. An illustrative application of GRDM is presented which evaluates how the optimal economic lives of analog and digital switching equipment change as the assumed date of widespread broadband switching availability is varied     

Coverage planning for optimizing HSDPA performance and?controlling R99 soft handover

Coverage planning is an important engineering task in deploying UMTS networks implementing both high speed downlink packet access (HSDPA) and Release 99 (R99) services. Coverage planning amounts to determining the cell coverage pattern by means of setting the common pilot channel (CPICH) power of the cells. A conventional strategy is to uniformly allocate a proportion of the total power to CPICH. In this paper, we develop mathematical modeling and optimization approaches to bring the benefit of power saving enabled by optimizing non-uniform CPICH to enhance HSDPA performance, while preserving a desired degree of soft handover (SHO) for R99. The study focuses on HSDPA performance at cell edges, where data throughput is typically low. An integer linear programming model is developed for the resulting optimization problem. The model admits optimal or near-optimal planning solutions for relatively small networks. Solution algorithms based on local search and repeated local search are developed. These algorithms are able to perform the optimization for large-scale networks time-efficiently. Experimental results for both synthesized networks as well as instances originating from real planning scenarios demonstrate the benefit of our optimization approach.     

Multiobjective water resources investment planning under budgetaryand socio-technical uncertainties

An integration of stochastic dynamic programming (SDP) and integer goal programming (IGP) modeling framework is proposed to handle problems of multiobjective-multicriteria sequential decision making under budgetary and socio-technical uncertainties inherent in water resources investment planning. In the proposed SDP model, probabilities of the funding levels in any time period that are generated using a subjective model are employed to handle budgetary fluctuations. This subjective model consists of historical data as a basic rate, functional relationships among inter-related parameters of the SDP model, scenarios of future budget availability, and subjective inputs elicited from a group of decision makers through a collective opinion technique. Application of the SDP model primarily yields an optimal investment planning policy that recognizes the possibility that actual funding received maybe less than that anticipated, and therefore the projects being implemented under the anticipated budget would be interrupted. In this integrated model, economic return of each level of investment decision together with its associated project portfolio is determined by the IGP model based on goals and criteria preferences with explicit consideration to socio-technical uncertainty     

A Scheme to Increase Throughput in Framed‐ALOHA‐Based RFID Systems with Capture

In this paper, a scheme to increase the throughput of RFID systems is presented, which considers the capture effect in the context of framed ALOHA protocol. Under the capture model in which the probability of one tag is identified successfully depending on the number of tags involved in the collision, two probabilistic methods for estimating the unknown number of tags are proposed. The first method is the maximum likelihood estimation method, and the second method is an approximate algorithm for reducing the computational time. The optimal frame size condition to maximize the system throughput by considering the capture effect is also presented.     

Forecasting electronic part procurement lifetimes to enable the management of DMSMS obsolescence

Many technologies have life cycles that are shorter than the life cycle of the product or system they are in. Life cycle mismatches caused by the obsolescence of technology can result in large life cycle costs for long field life systems, such as aircraft, ships, communications infrastructure, power plant and grid management, and military systems. This paper addresses Diminishing Manufacturing Sources and Materials Shortages (DMSMS) obsolescence, which is defined as the loss of the ability to procure a technology or part from its original manufacturer. Forecasting when technologies and specific parts will become unavailable (non-procurable) is a key enabler for pro-active DMSMS management and strategic life cycle planning for long field life systems. This paper presents a methodology for generating algorithms that can be used to predict the obsolescence dates for electronic parts that do not have clear evolutionary parametric drivers. The method is based on the calculation of procurement lifetime using databases of previous obsolescence events and introduced parts that have not gone obsolete. The methodology has been demonstrated on a range of different electronic parts and for the trending of specific part attributes.     

Efficient scheduling policies to reduce mean and variance ofcycle-time in semiconductor manufacturing plants

The problem of reducing the mean and variance of cycle time in semiconductor manufacturing plants is addressed. Such plants feature a characteristic reentrant process flow, where lots repeatedly return at different stages of their production to the same service stations for further processing, consequently creating much competition for machines. We introduce a new class of scheduling policies, called Fluctuation Smoothing policies. Unanimously, our policies achieved the best mean cycle time and Standard Deviation of Cycle Time, in all the configurations of plant models and release policies tested. As an example, under the recommended Workload Regulation Release policy, for a heavily loaded Research and Development Fabrication Line model, our Fluctuation Smoothing policies achieved a reduction of 22.4% in the Mean Queueing Time, and a reduction of 52.0% in the Standard Deviation of Cycle Time, over the baseline FIFO policy. These conclusions are based on extensive simulations conducted on two models of semiconductor manufacturing plants. The first is a model of a Research and Development Fabrication Line. The second is an aggregate model intended to approximate a full scale production line. Statistical tests are used to corroborate our conclusions     

Wireless information and power transfer using single and multiple path relays

A relay‐based wireless communication model can relay information along with the power bidirectionally using the amplify‐and‐forward scheme. This paper studies such model extensively. Three information and power relaying protocols, that is, time‐based switching relaying, power‐based splitting relaying, and hybrid time switching‐based and power splitting‐based relaying (HTPSR) are used to carry forward bidirectional information and power transfer. First, a solo relay model is studied, for which, we derived a throughput expression for end‐to‐end information transfer, and this is done for all the three relaying protocols. The paper indicates that the system throughput depends upon the time switching and the power splitting ratio. Further, to make the system more reliable and robust, multiple relays are used in the path. Various relay selection schemes are used for path selection in each transmission, thereby yielding different throughput performances. The results show that an optimal throughput is obtained for a given relay location at an optimal set of values of splitting and switching ratio. Moreover, the HTPSR outperforms both the power splitting and time switching protocol in system throughput performance for a single as well as a multiple‐relay model. Whereas, in relay selection schemes, the best SNR selection scheme outperforms in all the schemes used. The simulated results confirm that the system throughput is an active function of relay placement.     

Indoor Planning for High Speed Downlink Packet Access in WCDMA Cellular Network

The aim of this paper is to show the special characteristics of the indoor environment related to radio propagation and furthermore to radio network planning. The aspects of the radio network planning are highlighted especially for Wideband Code Division Multiple Access (WCDMA) radio access technology that is used widely in the third generation mobile networks. Moreover, the detailed planning parameters in indoor environment are studied for High Speed Downlink Packet Access (HSDPA) in order to support high throughput data applications in Universal Mobile Telecommunications System (UMTS). The final target of the paper is to compare pico cell, distributed antenna system (DAS), and radiating cable network configurations in indoor environment to provide the optimal radio conditions for the data applications, and thus to serve highest number of mobile users. Several measurement campaigns with different antenna configurations have been conducted in order to study the effect of multi path related parameters, as delay spread of the signal. Also other capacity related parameters as received signal levels, interference, throughput, and transmit power levels have been studied in order to find out the optimal solution for HSDPA in UMTS. The results clearly show that pico cells and distributed antenna system have outstanding performance in indoor propagation channel compared to radiating cable. In sense of signal quality, pico cell performance is slightly better compared to distributed antenna system. However, measurements with HSDPA indicate that practical capacity of DAS outperforms pico cells. The measurements also show that separation of the antennas is a key capacity related parameter when planning WCDMA based indoor systems.     

共边排样件激光切割路径的规划

排样软件的应用使材料利用率得到了很大提高，然而后续切割软件若不能保证有效地切割零件、保证零件质量及提高生产率，则排样软件在材料利用率上获得的收益将丧失。基于图论学理论，建立了规则与非规则零件共边排样时激光切割路径规划的数学模型，给出了在充分考虑加工质量、加工效率、制造成本情况下的激光切割路径优化目标：打孔点最少以及切割中割嘴空行程最短。提出了满足激光切割工艺要求的三个切割路径优化算法：用于求解理想情况下共边切割路径优化问题的一个新的欧拉回路算法；基于奇度顶点完全图最小权最大匹配算法来求解一般情况下共边切割路径优化问题的算法；利用废料区域进一步减少打孔点的处理策略与求解算法。给出了各种算法的运行实例，验证了所提出的算法的有效性。     

蜂窝网络数据业务模型的建立方法

马尔科夫随机过程是电路域业务模型的建立基础。本文首先阐述马尔科夫随机过程理论建立电路域模型业务模型的原理和方法,并指出该方法并不适用于基于信道共享的移动数据业务场景。然后,阐述了移动蜂窝网络的数据业务特征,并重新提出了一种新的数据业务模型,该模型结合了通信网络的实际性能和用户量,可以获得网络最佳在线用户数和最佳吞吐量,从而为移动数据业务的规划和优化奠定可靠的基础。