An integrated scheduling and control model for multi-mode projects

In today’s highly competitive uncertain project environments, it is of crucial importance to develop analytical models and algorithms to schedule and control project activities so that the deviations from the project objectives are minimized. This paper addresses the integrated scheduling and control in multi-mode project environments. We propose an optimization model that models the dynamic behavior of projects and integrates optimal control into a practically relevant project scheduling problem. From the scheduling perspective, we address the discrete time/cost trade-off problem, whereas an optimal control formulation is used to capture the effect of project control. Moreover, we develop a solution algorithm for two particular instances of the optimal project control. This algorithm combines a tabu search strategy and nonlinear programming. It is applied to a large scale test bed and its efficiency is tested by means of computational experiments. To the best of our knowledge, this research is the first application of optimal control theory to multi-mode project networks. The models and algorithms developed in this research are targeted as a support tool for project managers in both scheduling and deciding on the timing and quantity of control activities.     

Resource dedication problem in a multi-project environment

There can be different approaches to the management of resources within the context of multi-project scheduling problems. In general, approaches to multi-project scheduling problems consider the resources as a pool shared by all projects. On the other hand, when projects are distributed geographically or sharing resources between projects is not preferred, then this resource sharing policy may not be feasible. In such cases, the resources must be dedicated to individual projects throughout the project durations. This multi-project problem environment is defined here as the resource dedication problem (RDP). RDP is defined as the optimal dedication of resource capacities to different projects within the overall limits of the resources and with the objective of minimizing a predetermined objective function. The projects involved are multi-mode resource constrained project scheduling problems with finish to start zero time lag and non-preemptive activities and limited renewable and nonrenewable resources. Here, the characterization of RDP, its mathematical formulation and two different solution methodologies are presented. The first solution approach is a genetic algorithm employing a new improvement move called combinatorial auction for RDP, which is based on preferences of projects for resources. Two different methods for calculating the projects’ preferences based on linear and Lagrangian relaxation are proposed. The second solution approach is a Lagrangian relaxation based heuristic employing subgradient optimization. Numerical studies demonstrate that the proposed approaches are powerful methods for solving this problem.     

基于生态流方法的土地整治项目对农田生态系统的影响研究

将土地整治活动作为外界对农田生态系统(项目区)集中性的外部激励,以陕西关中凤翔县典型土地整治项目为例,分析了项目实施前后生态流(物质流、能量流、信息流)变化状况,建立了土地整治生态影响概念性模型,明确了相应生态流的流向与路径关系,使用可用能法和能值法测算项目区外部输入及生态产品输出,应用生态流分析法,对土地整治项目生态流和系统效率进行了定量计算。根据设定的土地整治工程使用年限,评估了项目实施后区域净生态价值、自然资源依赖度、可更新资源依赖度、生态产出率、生态承载力和生态可持续度等指标的时间变化过程。得到以下研究结果:(1)可用能法和能值法测算出的系统生态效益均呈现由项目建设初期陡降为负值,而后指数增加,再趋于平稳的过程;(2)可用能法测算出项目实施后的第29年,生态效益由亏转盈,体现出系统从被扰乱后恢复自然平衡状态的过程;(3)能值法测算出项目实施后的第4年,生态系统趋于平衡状态;(4)研究区土地整治项目的经济效益为负,于项目实施3a后趋于平稳,总投资中农业生产年投入占资金总额的78.35%。通过可用能和能值方法的结合,可以定量计算系统稳定性,为土地整治项目的物质、劳动力和资金投资选择等提供借鉴。     

An effective reliability-driven technique of allocating tasks on heterogeneous cluster systems

In large-scale heterogeneous cluster computing systems, processor and network failures are inevitable and can have an adverse effect on applications executing on such systems. One way of taking failures into account is to employ a reliable scheduling algorithm. However, most existing scheduling algorithms for precedence constrained tasks in heterogeneous systems only consider scheduling length, and not efficiently satisfy the reliability requirements of task. In recognition of this problem, we build an application reliability analysis model based on Weibull distribution, which can dynamically measure the reliability of task executing on heterogeneous cluster with arbitrary networks architectures. Then, we propose a reliability-driven earliest finish time with duplication scheduling algorithm (REFTD) which incorporates task reliability overhead into scheduling. Furthermore, to improve system reliability, it duplicates task as if task hazard rate is more than threshold \(\theta \) . The comparison study, based on both randomly generated graphs and the graphs of some real applications, shows that our scheduling algorithm can shorten schedule length and improve system reliability significantly.     

Modelling tropical fire ant (<Emphasis Type="Italic">Solenopsis geminata</Emphasis>) dynamics and detection to inform an eradication project

Invasive species threaten endangered species worldwide and substantial effort is focused on their control. Eradication projects require critical resource allocation decisions, as they affect both the likelihood of success and the overall cost. However, these complex decisions must often be made within data-poor environments. Here we develop a mathematical framework to assist in resource allocation for invasive species control projects and we apply it to the proposed eradication of the tropical fire ant (Solenopsis geminata) from the islands of Ashmore Reef in the Timor Sea. Our framework contains two models: a population model and a detection model. Our stochastic population model is used to predict ant abundance through time and allows us to estimate the probability of eradication. Using abundance predictions from the population model, we use the detection model to predict the probability of ant detection through time. These models inform key decisions throughout the project, which include deciding how many baiting events should take place, deciding whether to invest in detector dogs and setting surveillance effort to confirm eradication following control. We find that using a combination of insect growth regulator and toxins are required to achieve a high probability of eradication over 2 years, and we find that using two detector dogs may be more cost-effective than the use of lure deployment, provided that they are used across the life of the project. Our analysis lays a foundation for making decisions about control and detection throughout the project and provides specific advice about resource allocation.     

An ant-based coordination mechanism for resource-constrained project scheduling with multiple agents and cash flow objectives

We consider a multi-agent extension of the non-preemptive single-mode resource-constrained project scheduling problem with discounted cash flow objectives. Such a problem setting is related to project scheduling problems which involve different autonomous firms where project activities are uniquely assigned to the project parties (agents). Taking into account opportunistic agents and the resulting information asymmetry we propose a general decentralized negotiation approach which uses ideas from ant colony optimization. In the course of the negotiation the agents iteratively vote on proposed project schedules without disclosing preference information regarding cash flow values. Computational experiments serve to analyze the agent-based coordination mechanism in comparison to other approaches from the literature. The proposed mechanism turns out as an effective method for coordinating self-interested agents with conflicting goals which collaborate in resource-constrained projects.     

Game Theoretical Analysis on Cooperation Stability and Incentive Effectiveness in Community Networks

Community networks, the distinguishing feature of which is membership admittance, appear on P2P networks, social networks, and conventional Web networks. Joining the network costs money, time or network bandwidth, but the individuals get access to special resources owned by the community in return. The prosperity and stability of the community are determined by both the policy of admittance and the attraction of the privileges gained by joining. However, some misbehaving users can get the dedicated resources with some illicit and low-cost approaches, which introduce instability into the community, a phenomenon that will destroy the membership policy. In this paper, we analyze on the stability using game theory on such a phenomenon. We propose a game-theoretical model of stability analysis in community networks and provide conditions for a stable community. We then extend the model to analyze the effectiveness of different incentive policies, which could be used when the community cannot maintain its members in certain situations. Then we verify those models through a simulation. Finally, we discuss several ways to promote community network’s stability by adjusting the network’s properties and give some proposal on the designs of these types of networks from the points of game theory and stability.     

Project scheduling with resource capacities and requests varying with time: a case study

This paper discusses an extension of the classical resource-constrained project scheduling problem in which the resource availability as well as the resource request of the activities may change from period to period. While the applicability of this extension should be obvious, we provide a case study in order to emphasize the need for the extension. A real-world medical research project is presented which has a structure that is typical for many other medical and pharmacological research projects that consist of experiments. Subsequently, we provide a mathematical model and analyze some properties of the extended problem setting. We also introduce a new priority rule heuristic that is based on a randomized activity selection mechanism which makes use of so-called tournaments. Finally, we report our computational results for the original data of the medical research project as well as for a set of systematically generated test instances.     

Gradient Descent Optimization in Gene Regulatory Pathways

Background

Gene Regulatory Networks (GRNs) have become a major focus of interest in recent years. Elucidating the architecture and dynamics of large scale gene regulatory networks is an important goal in systems biology. The knowledge of the gene regulatory networks further gives insights about gene regulatory pathways. This information leads to many potential applications in medicine and molecular biology, examples of which are identification of metabolic pathways, complex genetic diseases, drug discovery and toxicology analysis. High-throughput technologies allow studying various aspects of gene regulatory networks on a genome-wide scale and we will discuss recent advances as well as limitations and future challenges for gene network modeling. Novel approaches are needed to both infer the causal genes and generate hypothesis on the underlying regulatory mechanisms.

Methodology

In the present article, we introduce a new method for identifying a set of optimal gene regulatory pathways by using structural equations as a tool for modeling gene regulatory networks. The method, first of all, generates data on reaction flows in a pathway. A set of constraints is formulated incorporating weighting coefficients. Finally the gene regulatory pathways are obtained through optimization of an objective function with respect to these weighting coefficients. The effectiveness of the present method is successfully tested on ten gene regulatory networks existing in the literature. A comparative study with the existing extreme pathway analysis also forms a part of this investigation. The results compare favorably with earlier experimental results. The validated pathways point to a combination of previously documented and novel findings.

Conclusions

We show that our method can correctly identify the causal genes and effectively output experimentally verified pathways. The present method has been successful in deriving the optimal regulatory pathways for all the regulatory networks considered. The biological significance and applicability of the optimal pathways has also been discussed. Finally the usefulness of the present method on genetic engineering is depicted with an example.     

MIP formulations for an application of project scheduling in human resource management

In the literature, various discrete-time and continuous-time mixed-integer linear programming (MIP) formulations for project scheduling problems have been proposed. The performance of these formulations has been analyzed based on generic test instances. The objective of this study is to analyze the performance of discrete-time and continuous-time MIP formulations for a real-life application of project scheduling in human resource management. We consider the problem of scheduling assessment centers. In an assessment center, candidates for job positions perform different tasks while being observed and evaluated by assessors. Because these assessors are highly qualified and expensive personnel, the duration of the assessment center should be minimized. Complex rules for assigning assessors to candidates distinguish this problem from other scheduling problems discussed in the literature. We develop two discrete-time and three continuous-time MIP formulations, and we present problem-specific lower bounds. In a comparative study, we analyze the performance of the five MIP formulations on four real-life instances and a set of 240 instances derived from real-life data. The results indicate that good or optimal solutions are obtained for all instances within short computational time. In particular, one of the real-life instances is solved to optimality. Surprisingly, the continuous-time formulations outperform the discrete-time formulations in terms of solution quality.     

Interbasin water transfer, riverine connectivity, and spatial controls on fish biodiversity

Background

Large-scale inter-basin water transfer (IBWT) projects are commonly proposed as solutions to water distribution and supply problems. These problems are likely to intensify under future population growth and climate change scenarios. Scarce data on the distribution of freshwater fishes frequently limits the ability to assess the potential implications of an IBWT project on freshwater fish communities. Because connectivity in habitat networks is expected to be critical to species'' biogeography, consideration of changes in the relative isolation of riverine networks may provide a strategy for controlling impacts of IBWTs on freshwater fish communities.

Methods/Principal Findings

Using empirical data on the current patterns of freshwater fish biodiversity for rivers of peninsular India, we show here how the spatial changes alone under an archetypal IBWT project will (1) reduce freshwater fish biodiversity system-wide, (2) alter patterns of local species richness, (3) expand distributions of widespread species throughout peninsular rivers, and (4) decrease community richness by increasing inter-basin similarity (a mechanism for the observed decrease in biodiversity). Given the complexity of the IBWT, many paths to partial or full completion of the project are possible. We evaluate two strategies for step-wise implementation of the 11 canals, based on economic or ecological considerations. We find that for each step in the project, the impacts on freshwater fish communities are sensitive to which canal is added to the network.

Conclusions/Significance

Importantly, ecological impacts can be reduced by associating the sequence in which canals are added to characteristics of the links, except for the case when all 11 canals are implemented simultaneously (at which point the sequence of canal addition is inconsequential). By identifying the fundamental relationship between the geometry of riverine networks and freshwater fish biodiversity, our results will aid in assessing impacts of IBWT projects and balancing ecosystem and societal demands for freshwater, even in cases where biodiversity data are limited.     

Evolution of Cooperation on Spatial Network with Limited Resource

Considering the external resource offered by environment is limited, here, we will explore the cooperation on spatial networks with limited resource. The individual distributes the limited resource according to the payoffs acquired in games, and one with resource amounts is lower than critical survival resource level will be replaced by the offspring of its neighbors. We find that, for larger temptation to defect, the number of the dead decreases with the resource amount. However the cooperation behavior is interesting, the lower total resource and intermediate temptation to defect can greatly promote the cooperation on square lattice. Our result reveals that the limited resource contributes most to the cooperation.     

The seasonal dynamic of ant‐flower networks in a semi‐arid tropical environment

1. Several studies have recently focused on the structure of ecological networks involving ants and plants with extrafloral nectaries; however, little is known about the effects of temporal variation in resource abundance on the structure of ant–plant networks mediated by floral nectar. 2. In this study, it was evaluated how strong seasonality in resource availability in a semi‐arid tropical environment affects the structure of ant–flower networks. We recorded ants collecting floral nectar during two seasons (from December 2009 to January 2013): dry and green seasons. Then, we built interaction networks for flower‐visiting ants in the Brazilian Caatinga separately for each combination of transect and season. 3. In general, strong seasonality directly influenced patterns of ant–flower interactions and the overall complexity of these ecological networks. During the dry season, networks were more connected, less modular, and exhibited greater niche overlap of flower‐visiting ants than during the green season. Moreover, resource utilisation by ants during the dry season tended to be more aggregated. These findings indicate that during the dry season, ant species tended to share many resource bases, probably owing to lower overall resource availability during this season. Species composition of the ant network component was highly season specific; however, a central core of highly generalised ants was present during both seasons. 4. The stability of this central core between seasons could strongly affect the ecological and evolutionary dynamics of these interaction networks. This study contributes to the understanding of the structure and dynamics of ant‐flower interactions in extremely seasonal environments.     

水利工程对坝下径流的影响——以葛洲坝、三峡水利枢纽为例

水利工程建设在给人类带来抗旱防洪效益、发电效益、航运效益、养殖等效益的同时,也对河流水文动态产生了一系列的影响,主要表现为对径流的调节。基于宜昌站1890—2014年径流数据,综合采用径流集中度、集中期和相位差分析等多种方法,分析了水利工程建设对径流年内分配以及枯水期的影响。结果表明:宜昌站径流集中度呈现缓慢下降趋势并在2004年发生突变,2003年以后径流集中度相对于2003年以前下降0.06(下降幅度为12.98%),说明葛洲坝水利枢纽、三峡工程建成以后宜昌站径流在年内分配变得平缓,洪峰被有效削弱,且三峡工程对宜昌站径流集中度减少的贡献率大于葛洲坝水利枢纽(贡献率分别为92.03%和7.97%);葛洲坝和三峡水利枢纽建成后,宜昌站径流重心提前8d(集中期从8月9日提前至7月31日);宜昌站进入枯水期的时间提前约20d(三峡大坝建设以前,宜昌站在12月7—11日进入枯水期,建设以后在11月底进入枯水期),水利工程对水文过程的影响可能导致下游枯水期污染加剧和湿地生境提前缩小,进而影响下游水环境和湿地生物多样性。上述结果定量揭示了水利工程对水文过程的影响及其潜在生态效应,可为认识水利工程的生态影响以及流域生态环境变化的驱动因素提供科学依据。     

Scaling in Transportation Networks

Subway systems span most large cities, and railway networks most countries in the world. These networks are fundamental in the development of countries and their cities, and it is therefore crucial to understand their formation and evolution. However, if the topological properties of these networks are fairly well understood, how they relate to population and socio-economical properties remains an open question. We propose here a general coarse-grained approach, based on a cost-benefit analysis that accounts for the scaling properties of the main quantities characterizing these systems (the number of stations, the total length, and the ridership) with the substrate''s population, area and wealth. More precisely, we show that the length, number of stations and ridership of subways and rail networks can be estimated knowing the area, population and wealth of the underlying region. These predictions are in good agreement with data gathered for about subway systems and more than railway networks in the world. We also show that train networks and subway systems can be described within the same framework, but with a fundamental difference: while the interstation distance seems to be constant and determined by the typical walking distance for subways, the interstation distance for railways scales with the number of stations.     

The US Virtual Herbarium: working with individual herbaria to build a national resource

The goal of the US Virtual Herbarium (USVH) project is to digitize (database, image, georeference) all specimens in all US herbaria, enabling them to be made available through a single portal. Herbaria house specimens of plants, fungi, and algae, so USVH will offer a rich portrait of biodiversity in the US and in the other countries represented in US herbaria. Equally importantly, working towards this goal will engage people with herbaria and the organisms they house, expanding their appreciation of both the power of biodiversity informatics and the demands that it places on data providers while developing improved communication among those working in and with herbaria. The project is not funded but has strong support among those working in herbaria. It works through regional herbarium networks, some of which existed prior to the USVH project, while others are still in gestation. It differs from most digitization projects in its emphasis on helping those involved with herbaria become part of a national enterprise, an aspect that is seen as critical to creating the resources needed to develop and sustain the project. In this paper, we present some of the lessons we have learned and the difficulties we have encountered during the first few years of the project.     

Ectoparasitic "jacks-of-all-trades": relationship between abundance and host specificity in fleas (Siphonaptera) parasitic on small mammals

Animal species with larger local populations tend to be widespread across many localities, whereas species with smaller local populations occur in fewer localities. This pattern is well documented for free-living species and can be explained by the resource breadth hypothesis: the attributes that enable a species to exploit a diversity of resources allow it to attain a broad distribution and high local density. In contrast, for parasitic organisms, the trade-off hypothesis predicts that parasites exploiting many host species will achieve lower mean abundance on those hosts than more host-specific parasites because of the costs of adaptations against multiple defense systems. We test these alternative hypotheses with data on host specificity and abundance of fleas parasitic on small mammals from 20 different regions. Our analyses controlled for phylogenetic influences, differences in host body surface area, and sampling effort. In most regions, we found significant positive relationships between flea abundance and either the number of host species they exploited or the average taxonomic distance among those host species. This was true whether we used mean flea abundance or the maximum abundance they achieved on their optimal host. Although fleas tended to exploit more host species in regions with either larger number of available hosts or more taxonomically diverse host faunas, differences in host faunas between regions had no clear effect on the abundance-host specificity relationship. Overall, the results support the resource breadth hypothesis: fleas exploiting many host species or taxonomically unrelated hosts achieve higher abundance than specialist fleas. We conclude that generalist parasites achieve higher abundance because of a combination of resource availability and stability.     

A mathematical model for pest management in Jatropha curcas with integrated pesticides - An optimal control approach

This paper presents the formulation and analysis of a mathematical model for Jatropha curcas plantation with a view to control its natural pests using application of integrated pesticides. Bio-pesticides are costly, require a long term process and expensive to impose. But if chemical pesticides are introduced in the farming system along with bio-pesticide, the process will be faster as well as cost effective. Here, we study the control of pests using integrated approach i.e. using combination of bio-pesticides and chemical pesticides. We identify the parameter for which stability switches may occur. Finally, optimal concentration profile of both pesticides have been determined using optimal control theory to minimize it negative effects and also to make the process cost effective. Numerical simulations justify the main results.     

Block‐cyclic redistribution over heterogeneous networks

Clusters of workstations and networked parallel computing systems are emerging as promising computational platforms for HPC applications. The processors in such systems are typically interconnected by a collection of heterogeneous networks such as Ethernet, ATM, and FDDI, among others. In this paper, we develop techniques to perform block-cyclic redistribution over P processors interconnected by such a collection of heterogeneous networks. We represent the communication scheduling problem using a timing diagram formalism. Here, each interprocessor communication event is represented by a rectangle whose height denotes the time to perform this event over the heterogeneous network. The communication scheduling problem is then one of appropriately positioning the rectangles so as to minimize the completion time of all the communication events. For the important case where the block size changes by a factor of K, we develop a heuristic algorithm whose completion time is at most twice the optimal. The running time of the heuristic is O(PK ²). Our heuristic algorithm is adaptive to variations in network performance, and derives schedules at run-time, based on current information about the available network bandwidth. Our experimental results show that our schedules always have communication times that are very close to optimal. This revised version was published online in July 2006 with corrections to the Cover Date.     

Design and Performance Analysis of Divisible Load Scheduling Strategies on Arbitrary Graphs

In this paper, we consider the problem of scheduling divisible loads on arbitrary graphs with the objective to minimize the total processing time of the entire load submitted for processing. We consider an arbitrary graph network comprising heterogeneous processors interconnected via heterogeneous links in an arbitrary fashion. The divisible load is assumed to originate at any processor in the network. We transform the problem into a multi-level unbalanced tree network and schedule the divisible load. We design systematic procedures to identify and eliminate any redundant processor–link pairs (those pairs whose consideration in scheduling will penalize the performance) and derive an optimal tree structure to obtain an optimal processing time, for a fixed sequence of load distribution. Since the algorithm thrives to determine an equivalent number of processors (resources) that can be used for processing the entire load, we refer to this approach as resource-aware optimal load distribution (RAOLD) algorithm. We extend our study by applying the optimal sequencing theorem proposed for single-level tree networks in the literature for multi-level tree for obtaining an optimal solution. We evaluate the performance for a wide range of arbitrary graphs with varying connectivity probabilities and processor densities. We also study the effect of network scalability and connectivity. We demonstrate the time performance when the point of load origination differs in the network and highlight certain key features that may be useful for algorithm and/or network system designers. We evaluate the time performance with rigorous simulation experiments under different system parameters for the ease of a complete understanding.