Optimal maintenance planning and crew allocation for multipurpose batch plants

A mathematical programming approach to optimize process plant performance subject to equipment failure is presented. The optimal production planning and scheduling in multipurpose process plants involves the efficient utilization of assets and resources to produce a number of products so as to satisfy market demands while optimizing a performance criterion. However, the degree of utilization of process plant components, within the time horizon of operation, critically depends on the level of equipment availability. The interactions between production and maintenance planning as well as the necessary links to quantify the strong interactions between them are studied. The preventive maintenance planning and crew allocation problem are used to demonstrate the effectiveness of the proposed approach. The overall problem is first formulated as an optimal control problem by integrating an aggregate production planning model with a continuous time Markov chain maintenance model. The resulting problem is then transformed into a mixed-integer linear programming model by using an Euler discretization scheme and appropriate linearizations of bilinear terms. Finally, extensions to include design aspects are also discussed. The applicability of the proposed approach is demonstrated by a number of illustrative examples.     

A thermal elastic model for constrained crystal growth with facets

A model for computing thermal stress inside a crystal with facets is presented. Using a systematical perturbation analysis, a semi-analytical thermal-stress solution is obtained for constrained directional growth with small lateral heat flux. This solution can be applied to crystals grown by various growth techniques such as the Czochralski method. The semi-analytical nature of the solution leads to a much more efficient approach for computing thermal stress in crystals with facets, compared to a full 3D simulation. Examples are given for crystals pulled in a variety of seed orientations.     

Dynamic and static job allocation for multi-server systems

We consider the optimal assignment of groups of jobs to a fixed number of time periods over a finite horizon to minimize the total facility idling and job waiting costs. The capacity of the facility varies randomly in the sense that the time that each one of the multiple servers becomes available is random (servers arrive late). The service times are also random and are independent and identically distributed. With approximations, we formulate a dynamic optimization model for this problem. With a simple modification, we can apply this dynamic model to a static outpatient appointment problem. We propose two methods to compute the capacity distribution: (1) Poisson approximation and (2) simulation. While the Poisson approximation works well for exponential service times, the simulation scheme enables us to use the dynamic model without actually specifying the service time distribution. The performance measures of the schedules obtained with these two methods compare well with those of the optimal allocation obtained from (exhaustive) simulation. We also conduct numerical studies to investigate the dynamics between the idling and waiting costs ratio and the number of scheduling periods.     

Stochastic dynamic programming model for optimal resource allocation in vehicular ad hoc networks

Vehicular ad hoc network (VANET) is an emerging trend where vehicles communicate with each other and possibly with a roadside unit to assist various applications like monitoring, managing and optimizing the transportation system. Collaboration among vehicles is significant in VANET. Resource constraint is one of the great challenges of VANETs. Because of the absence of centralized management, there is pitfall in optimal resource allocation, which leads to ineffective routing. Effective reliable routing is quite essential to achieve intelligent transportation. Stochastic dynamic programming is currently employed as a tool to analyse, develop and solve network resource constraint and allocation issues of resources in VANET. We have considered this work as a geographical-angular-zone-based two-phase dynamic resource allocation problem with a homogeneous resource class. This work uses a stochastic dynamic programming algorithm based on relaxed approximation to generate optimal resource allocation strategies over time in response to past task completion status history. The second phase resource allocation uses the observed outcome of the first phase task completion to provide optimal viability in resulting decisions. The proposed work will be further extended for the scenario that deals with heterogeneous resource class. Simulation results show that the proposed scheme works significantly well for the problems with identical resources.     

A unified constrained inversion model for ultrasonic flaw sizing

Equivalent flaw sizing using ultrasonic waves is an approach whereby shape and orientation information of a defect are obtained in terms of a best-fit simple geometry that is able to represent the major aspects of the flaw. Separate examples of this approach have previously been developed for volumetric flaws and cracks using the Born and Kirchhoff approximations, respectively. Here, these separate algorithms are unified into a single algorithm capable of sizing both volumetric flaws and cracks. Some examples of the performance of this unified algorithm on both synthetic and experimental data are also given.     

一个面向异构多核处理器Cell的资源分配模型

为了充分利用多核处理器提供的多级并行和解决多核资源分配问题,提出了一种将多任务并行程序映射到多核处理器平台上的模型驱动的方法。该方法首先创建一个三维优化空间来表示资源分配配置,而后通过搜索该空间为应用生成多种并行机制,最后对各种并行机制进行静态评估从而找出最优的机制。该方法同时考虑了任务并行、数据并行以及通讯开销。在异构多核处理器Cell上利用一个图像处理应用对此方法进行了测试。实验表明,这种模型驱动的方法能够很好地评估性能并为应用确定有效的并行机制。     

A stochastic equipment capacity model

This paper presents a model for the determination of the optimal equipment capacity for situations where a stochastic demand of Bervicea can be met by both owned equipment operating on a regular and overtime basis and hired-in equipment from an external source.     

基于FDMA系统的两跳中继网络的资源分配

首先介绍了一种可用于两跳中继网络的时分模式帧结构,然后基于该帧结构提出了一种资源分配算法.该算法包括两个步骤:第一个步骤是第一个时隙上的动态资源分配,第二个步骤是基站与中继站之间的最优化功率分配.两跳中继网络中下行存在三种链路:"基站-中继"链路、"基站-用户"链路和"中继-用户"链路,在系统资源有限的条件下,通过所提算法为这三种链路分配相应的带宽和功率,可以使得系统的吞吐量最大.仿真结果表明所提算法能够有效地提高系统的吞吐量.     

Cost optimal segregated targeting for resource allocation networks

In this paper, a generalised methodology is proposed to target cost optimal allocation of resources in segregated targeting problems. Cost optimal segregated targeting problems are characterised by the existence of multiple zones; each consisting of a set of demands and using a unique resource with given cost and a single quality index (e.g., emissions factor, contaminant concentrations, etc.). All these zones share a common set of internal sources. This paper presents a rigorous mathematical proof of the decomposition principle that decomposes the problem into a sequence of sub-problems. Decomposition of the original problem is performed based on the prioritised costs for each external resource, attached to a particular zone. Prioritised cost of a resource depends on the pinch quality, quality of the resource and its cost. Applicability of the proposed methodology is illustrated by examples from carbon-constrained energy planning and water allocation networks.     

A Multiple objective shift allocation model

This paper is concerned with a production planning problem of allocating production items to production shifts on production lines in a multiple objective decision environment. The problem is modeled and solutions are generated using integer goal programming techniques. Objectives are formulated not only in terms of minimizing the sum of deviations from goal target levels, but also in terms of minimizing the maximum deviation. Test results indicate that the model structure and solution process utilized can provide decision makers with a good set of representative solutions in a rather complex multiple objective decision environment.     

A bi-objective model for robust yard allocation scheduling for outbound containers

This article examines the yard allocation problem for outbound containers, with consideration of uncertainty factors, mainly including the arrival and operation time of calling vessels. Based on the time buffer inserting method, a bi-objective model is constructed to minimize the total operational cost and to maximize the robustness of fighting against the uncertainty. Due to the NP-hardness of the constructed model, a two-stage heuristic is developed to solve the problem. In the first stage, initial solutions are obtained by a greedy algorithm that looks n-steps ahead with the uncertainty factors set as their respective expected values; in the second stage, based on the solutions obtained in the first stage and with consideration of uncertainty factors, a neighbourhood search heuristic is employed to generate robust solutions that can fight better against the fluctuation of uncertainty factors. Finally, extensive numerical experiments are conducted to test the performance of the proposed method.     

Ad hoc网络中一种跨层流量分配算法——CLATA

针对ad hoc网络各协议层的功能都相互关联的特点,提出了一种在ad hoc网络中基于网络平均时延最小的跨层自适应流量分配算法（CLATA）。该算法将网络层自适应流量分配信息传递给媒体接入控制（MAC）层,以改进MAC层中的冲突退避算法,实现网络平均时延最小化,提高网络的利用率。仿真实验结果表明,该算法可以动态调整链路之间的流量,并具有快速的自适应性,优化网络资源的利用。     

A bi-objective robust model for emergency resource allocation under uncertainty

Emergency resource allocation constitutes one of the most critical elements of response operations in the field of emergency management. This paper addresses an emergency resource allocation problem which involves multiple competing affected areas and one relief resource centre under supply shortage and uncertainty in the post-disaster phase. In humanitarian situations, both the efficiency and fairness of an allocation policy have a considerable influence on the effectiveness of emergency response operations. Thus, we formulate a bi-objective robust emergency resource allocation (BRERA) model which tries to maximise efficiency as well as fairness under different sources of uncertainties. To obtain decision-makers’ most preferred allocation policy, we propose a novel emergency resource allocation decision method which consists of three steps: (1) develop a bi-objective heuristic particle swarm optimisation algorithm to search the Pareto frontier of the BRERA model; (2) select a coefficient to measure fairness; and (3) establish a decision method based on decision-makers’ preference restricted by the fairness coefficient. Finally, a real case study taken from the 5 December 2008 Wenchuan Earthquake demonstrates the effectiveness of the proposed method through numerical results. The solution and model robustness are also analysed.     

A location-routing-inventory model for designing multisource distribution networks

This article studies a ternary-integration problem that incorporates location, inventory and routing decisions in designing a multisource distribution network. The objective of the problem is to minimize the total cost of location, routing and inventory. A mixed-integer programming formulation is first presented, and then a three-phase heuristic is developed to solve large-sized instances of the problem. The numerical study indicates that the proposed heuristic is both effective and efficient.     

A novel normal walk model for PCS networks with mesh cell configuration

Abstract

Model‐based movement patterns play a crucial role in evaluating the performance of mobility‐dependent Personal Communication Service (PCS) strategies, such as location updating and paging schemes. In this study, we propose a novel normal walk model to represent the daily mobility patterns of a mobile station (MS) in mesh PCS networks more closely than does a conventional random walk model. The proposed model applies a drift angle, θ, to determine the next relative direction in which an MS will leave a mesh cell in one step, based on the concepts that most real trips follow the shortest path and the directions of daily motion are mostly symmetric. Thus, the probability of θ is assumed to approach a normal distribution with the parameters: μ is set to 0° and σ falls in the interval [5°, 90°]. Varying σcan redistribute the probabilities of θ to make the movement patterns more realistic to represent the mobility of users in PCS networks.

An analytical normal walk model is further formulated in a 6‐layer cluster with mesh cells for quantitative analysis. Experimental results demonstrate that for σ = 10°, 30°, 60°, and 90°, the discrepancies between the analytical computations (expected steps) and the simulated values (average steps) are all within ±0.55%, and most are within ±0.35%. Moreover, when σ is set to 79.5°, a normal walk can almost represent and even replace a random walk.     

Scheduling advance reservation requests for wavelength division multiplexed networks with static traffic demands

Telecommunication and grid computing applications demand high bandwidth data channels that offer guarantees with respect to service availability. Such applications include: remote surgery, remote experimentation, video on-demand, teleconferencing and bulk transfers. Furthermore, by forecasting traffic patterns internet service providers attempt to optimise network resources in order to lower operational costs during peak periods of bandwidth consumption. Advance reservation for wavelength division multiplexed networks can address some of these issues by reserving high volume communication channels (i.e. lightpaths) beforehand. The authors develop a mathematical model to solve the problem of scheduling lightpaths in advance. The optimal solution is presented as a mixed integer linear program with the assumption that all traffic is static and the network is centrally controlled. Furthermore, we have developed two novel meta-heuristics based on: 1) a greedy implementation (local search) and 2) simulated annealing. The meta-heuristics have shown to produce good approximate solutions in a reasonable amount of time.     

主动约束层阻尼梁结构的应力连续模型

考虑到较厚的阻尼层内高阶剪切效应不应忽略,使用Reddy的三阶位移场描述阻尼层的纵向位移,使得在分界面上不仅位移连续,而且应力连续,从而提出ACLD结构的一种新模型“应力连续模型”。在此基础上,使用谱有限元法(SFEM)对ACLD梁结构进行力学建模和数值模拟,并与传统Mead-Markus模型结果进行了比较。研究表明,应力连续模型在固有频率和模态损耗因子预测上优于传统Mead-Markus模型。     

A model for the static fracture toughness of ductile structural steel

Fracture of ductile structural steels generally occurs after void initiation, void growth and void coalescence. In order for ductile fracture of structural steels to occur, energy must be spent to induce void initiation and void growth. Therefore, fracture toughness for ductile fracture should be contributed from void initiation and void growth. On the basis of this suggestion static fracture toughness (K_IC) of ductile structural steels is decomposed into two parts: void nucleation-induced fracture toughness (denoted as K_IC.n) and void growth-induced fracture toughness (K_IC.g). K_IC.n, defined as the stress intensity factor at which voids ahead of a crack begins to form, is calculated from crack tip strain distribution and void nucleation strain distribution. In contrast, K_IC.g is determined by the void growth from the beginning of void nucleation to void coalescence. Therefore, K_IC.g relates to the void sizes and void distribution. In this paper, the expression for K_IC.g is given from the void sizes directly from fracture surfaces. The relationship between K_IC.n, K_IC.g and K_IC is expressed in the form (K_IC)²=(K_IC.n)²+(K_IC.g)². The newly developed model was applied to the fracture toughness evaluation of three structural steels (SN490, X65 and SA440), and the theoretical calculation agrees with the experimental results.     

A model for the static fracture toughness of ductile structural steel

Fracture of ductile structural steels generally occurs after void initiation, void growth and void coalescence. In order for ductile fracture of structural steels to occur, energy must be spent to induce void initiation and void growth. Therefore, fracture toughness for ductile fracture should be contributed from void initiation and void growth. On the basis of this suggestion static fracture toughness (K_IC) of ductile structural steels is decomposed into two parts: void nucleation-induced fracture toughness (denoted as K_IC.n) and void growth-induced fracture toughness (K_IC.g). K_IC.n, defined as the stress intensity factor at which voids ahead of a crack begins to form, is calculated from crack tip strain distribution and void nucleation strain distribution. In contrast, K_IC.g is determined by the void growth from the beginning of void nucleation to void coalescence. Therefore, K_IC.g relates to the void sizes and void distribution. In this paper, the expression for K_IC.g is given from the void sizes directly from fracture surfaces. The relationship between K_IC.n, K_IC.g and K_IC is expressed in the form (K_IC)²=(K_IC.n)²+(K_IC.g)². The newly developed model was applied to the fracture toughness evaluation of three structural steels (SN490, X65 and SA440), and the theoretical calculation agrees with the experimental results.     

The buffer allocation problem for general finite buffer queueing networks

The Buffer Allocation Problem (BAP) is a difficult stochastic, integer, nonlinear programming problem. In general, the objective function and constraints of the problem are not available in a closed form. An approximation formula for predicting the optimal buffer allocation is developed based upon a two-moment approximation formula involving the expressions for M/ M/1/ K systems. The closed-form expressions of the M/ M/1/ K and M/ G/1/ K systems are utilized for the BAP in series, merge, and splitting topologies of finite buffer queueing networks. Extensive computational results demonstrate the efficacy of the approach.