A bi-objective hierarchical program scheduling problem and its solution based on NSGA-III

In enterprise project management systems, a program at the tactical level coordinates and manages multiple projects at the operational level. There are close relationships between multiple projects in a program, which are typically manifested as shared resources and precedence relationships. Most research efforts have concentrated on the resource sharing by projects, while the precedence relationships between projects have yet to be comprehensively investigated. In this paper, a bi-objective hierarchical resource-constrained program scheduling problem proposed, where both resource sharing and precedence relationships between projects are considered in a distributed environment. The problem contains two different sub-problems at the operational level and the tactical level, and they are modeled in the same way as two bi-objective multi-mode scheduling problems. Shared resources are allocated from the tactical level to the operational level, and once they are allocated to a project, they can only be re-allocated to other projects once the current project is finished. Subsequently, a two-phase algorithm based on NSGA-III is developed. The algorithm runs at the operational level and the tactical level in turn. According to the Pareto fronts of projects that are submitted from the operational level, the bi-objective program planning at the tactical level is conducted under the constraints of precedence relationships and shared resources. The results of computational simulations demonstrate the satisfactory performance of the improved algorithm. By coordinating the local optimization of projects and the global optimization of the program in a hierarchical framework, the method proposed in this paper provides an effective integrated scheduling method for decision-makers at various levels of a program.

     

A Vision for What Science Education Should Be Like for the First 25 Years of a New Millennium

Robert Yager is a native Iowan who was worked at the University of Iowa since 1956. He has served as president of seven national associations, including the National Science Teachers Association, School Science and Mathematics Association, the National Association of Biology Teachers, the Association for the Education of Teachers of Science, the National Association for Research in Science Teaching, Section Q of the American Association for the Advancement of Science, and the National Association of Science‐Technology‐Society. Yager has directed over 100 projects supported by the National Science Foundation, several research projects supported by the U.S. Department of Education, and several project evaluations. The University of Iowa has one of the largest graduate programs in the U.S., while also focusing on in‐service programs for science teachers and a model preservice program (which enjoyed NSF support for a 10‐year period). Yager has published over 500 books, monographs, and research reports. Currently, he is active with several research projects in Korea, Japan, Thailand, Malaysia, Israel, and Estonia.     

Competence-driven project portfolio selection,scheduling and staff assignment

This paper presents a new model for project portfolio selection, paying specific attention to competence development. The model seeks to maximize a weighted average of economic gains from projects and strategic gains from the increment of desirable competencies. As a sub-problem, scheduling and staff assignment for a candidate set of selected projects must also be optimized. We provide a nonlinear mixed-integer program formulation for the overall problem, and then propose heuristic solution techniques composed of (1) a greedy heuristic for the scheduling and staff assignment part, and (2) two (alternative) metaheuristics for the project selection part. The paper outlines experimental results on a real-world application provided by the E-Commerce Competence Center Austria and, for a slightly simplified instance, presents comparisons with the exact solution computed by CPLEX.     

Project selection,scheduling and resource allocation with time dependent returns

In this paper we formulate and analyze the joint problem of project selection and task scheduling. We study the situation where a manager has many alternative projects to pursue such as developing new product platforms or technologies, incremental product upgrades, or continuing education of human resources. Project return is assumed to be a known function of project completion time. Resources are limited and renewable. The objective is to maximize present worth of profit. A general mathematical formulation that can address several versions of the problem is presented. An implicit enumeration procedure is then developed and tested to provide good solutions based on project ordering and a prioritization rule for resource allocation. The algorithm uses an imbedded module for solving the resource-constrained project scheduling problem at each stage. The importance of integrating the impact of resource constraints into the selection of projects is demonstrated.     

Skill-based framework for optimal software project selection and resource allocation

This paper presents a conceptual framework and a mathematical formulation for software resource allocation and project selection at the level of software skills. First, we introduce a skill-based framework that considers universities, software companies, and potential projects of a country. Based on this framework, we formulate a linear integer program PMax which determines the selection of projects and the allocation of human resources that maximize profit for a certain company. We show that PMax is NP-complete. Therefore, we devise a meta-heuristic, called Tabu Select and Greedily Allocate (TSGA), to overcome the computational complexities. When compared to PMax running on CPLEX, TSGA performs 15 times faster with an accuracy of 98% on small to large size problems where CPLEX converges. On larger problems where CPLEX does not return an answer, TSGA computes a feasible solution in the order of minutes.     

公路工程评标中的模糊一致矩阵方法

公路工程评标是一项多目标的复杂决策过程,在公路工程多方案分析评价的层次分析决策中应用模糊一致矩阵方法,有效的避开了模糊综合评判中隶属度确定问题.为公路工程评价方案决策这类定性与定量因素并存、正相关与负相关混杂的多因素、多层次评价提供了另一类有效的评判方法,通过公路工程评标方案的分析得到公路工程方案的排序结果,实例分析证明模糊一致矩阵方法是可行的.     

Efficient preprocessing for VLSI optimization problems

Advances in technology for the manufacturing of integrated circuits have resulted in extremely large, and time consuming, problems on how to lay out components for optimal circuit performance. These problems can be written as mixed integer programs which are easily relaxed to linear programs with a very high number of variables and constraints. The relaxed programs can often be solved by applying state-of-the-art linear programming software, however these solutions come at the expense of long solution time. In this paper we show that, by considering the structure inherent in VLSI problems, one can specialize classical preprocessing algorithms to take into account the standard form of the constraint matrix for VLSI problems, thereby achieving improved preprocessing results with relatively little effort. We provide analysis showing our preprocessing techniques are accurate and provide some numerical testing demonstrating the increased efficiency. The numerical tests also demonstrate that using our preprocessing in conjunction with internal preprocessing methods that come with many linear program solvers, can improve the overall performance of the linear program solver and its preprocessor.     

Systemic risk assessment: a case study

Project Risk Registers have been used extensively for many years. However, they do not account for the interaction between risks, for example, the occurrence of one risk exacerbating other risks or portfolios of risks being more significant than the sum of the individual risks. This leads to the need to consider ‘risk systemicity’ as a part of risk analysis. This paper reports on a specific case for a large multinational project based organization, one that the authors had been involved with in the analysis of a number of projects that had massive cost overruns. Following these analyses the organization was persuaded of the importance of risk systemicity. The organization therefore engaged the authors to develop a ‘Risk Filter’. This filter is a tool for identifying areas of risk exposure on future projects and creating a framework for their investigation. The ‘Risk Filter’ is now used on all projects ever since its introduction; by the end of May 2003 it had been used by nine divisions, on over 60 major projects, and completed by 450 respondents. It is also used at several stages during the life of a project to aid in the risk assessment and management of each project, and contributes to a project database.     

Solving project scheduling problem with the philosophy of fuzzy random programming

Project scheduling problem is to determine the schedule of allocating resources to achieve the trade-off between the project cost and the completion time. In real projects, the trade-off between the project cost and the completion time, and the uncertainty of the environment are both considerable aspects for managers. Due to the complex external environment, this paper considers project scheduling problem with coexisted uncertainty of randomness and fuzziness, in which the philosophy of fuzzy random programming is introduced. Based on different ranking criteria of fuzzy random variables, three types of fuzzy random models are built. Besides, a searching approach by integrating fuzzy random simulations and genetic algorithm is designed for searching the optimal schedules. The goal of the paper is to provide a new method for solving project scheduling problem in hybrid uncertain environments.     

Uncertainty Modelling in Software Development Projects (With Case Study)

A project scheduling model tailored specifically for software development projects is proposed in this study. The model incorporates uncertainties related to activity durations and network topology. The first type of uncertainty exists due to error-prone coding which might result in elongated task durations caused by validation and debugging sessions. Furthermore, in practice, macro-activities represent groups of sub-tasks in order to simplify the planning and monitoring of the project. Due to the aggregation, it is more difficult to be precise on the duration of a macro-activity.The uncertainty related to the network topology is due to common database design issues or program modules shared among parallel tasks in the project network. These tasks become associated with each other through uncertain Start-to-Start (SS) precedence relationships. On the other hand, SS lags may also be the outcome of technological precedence relationships among pairs of activities. However, the imprecision underlying the work content of a predecessor activity leads to uncertain SS lags.Software development projects are human-intensive projects and hence, the duration of a task depends on the skill of the person assigned to the job as well as his/her learning rate. Thus, a task may be realized by alternative staff members which results in different expected task durations. Hence, a realistic model proposed for software development projects should incorporate staff assignment features under the uncertainties discussed above. In this study, we develop a mathematical model for software development projects and propose heuristic solution methods to be used by the project co-ordinator in preparing the project plan. The heuristic algorithms developed here are tested on real data provided by a consulting firm undertaking software development projects from manufacturing companies in Turkey.     

Automated solution of differential equations

Differential equations are solved routinely by large computer programs, but the solution process is rarely automated. Each equation requires a different program and each such program requires a considerable amount of work to develop and maintain. The FEniCS project provides a set of tools that automate important aspects of the solution process, ultimately aiming at a complete automation of computational mathematical modeling, including the automation of discretization, discrete solution, error control, modeling and optimization. A key component of FEniCS is the FEniCS Form Compiler (FFC), which automates the discretization of differential equations by taking as input a variational problem in mathematical notation and generating highly efficient optimized low-level code for the evaluation of the corresponding discrete operator. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Survey of computer programs for heat transfer analysis

An overview is given of the current capabilities of thirty-three computer programs that are used to solve heat transfer problems. The programs considered range from large general-purpose codes with broad spectrum of capabilities, large user community, and comprehensive user support (e.g., ABAQUS, ANSYS, EAL, MARC, MITAS II, MSC/NASTRAN, and SAMCEF) to the small, special-purpose codes with limited user community such as ANDES, NTEMP, TAC2D, TAC3D, TEPSA and TRUMP. The majority of the programs use either finite elements or finite differences for the spatial discretization. The capabilities of the programs are listed in tabular form followed by a summary of the major features of each program. The information presented herein is based on a questionnaire sent to the developers of each program. This information is preceded by a brief background material needed for effective evaluation and use of computer programs for heat transfer analysis.The present survey is useful in the initial selection of the programs which are most suitable for a particular application. The final selection of the program to be used should, however, be based on a detailed examination of the documentation and the literature about the program.     

A pathological semi-infinite program verifying Karlovitz's conjecture

In 1965, Duffin and Karlovitz approximated semi-infinite linear programs by a sequence of linear programs where thenth approximating program minimizes the objective function, subject to the firstn constraints. At that time, Karlovitz conjectured the existence of a semi-infinite convex program without a duality gap, whose approximating programs have a duality gap. The purpose of this note is to provide such an example.The author completed this work while at the University of Illinois at Urbana-Champaign, Illinois.     

An approximate solution approach for a scenario-based capital budgeting model

Real options techniques such as contingent claims analysis and dynamic programming can be used for project evaluation when the project develops stochastically over time and the decision to invest into this project can be postponed. Following that perspective, Meier et al. (Oper Res 49(2):196–2 06, 2001) presented a scenario based model that captures risk uncertainty and managerial flexibility, maximizing the time-varying of a portfolio of investment options. However, the corresponding linear integer program turns out to be quite intractable even for a small number of projects and time periods. In this paper, we propose a heuristic approach based on an alternative scenario based model involving a much less number of variables. The new approach allows the determination of reasonable quality approximate solutions with huge reductions on the computational times required for solving large size instances.     

A Locally Based Science Mentorship Program For High Achieving Students: Unearthing Issues That Influence Affective Outcomes

Little is known about the impact of university-situated science mentoring programs on the affect of high achieving high school students, and few science mentorship programs have been described. This study describes a university-based summer science mentorship program designed to offer participants a challenging science research experience and identifies issues that influence the affective outcomes for participants. Interview data was collected from eight participants at the 2nd and 6th weeks of participation. Student responses were summarized and iteratively searched to identify patterns within the responses for each interview. It was found that mentors played a crucial role in framing the participants' experience and influencing their affect and that careful selection and timing of research projects was critical to participants' attitude of learning and accomplishment. The implications for science mentorship program developers and for research are discussed.     

The use of advance demand information in a project-based supply chain

In a project environment, a manufacturer is confronted with two types of demand: regular demand from many small orders and very irregular, lumpy demand from infrequent, large orders. Manufacturers who build to stock must carry large safety stocks to meet the lumpy demand. As part of the project engineering process, however, project engineers and implementers (e.g. installers) typically have developed information about material requirements well in advance of placement of orders. We analyze the inventory reduction that could be achieved if the installer were to communicate advance demand information (ADI) to the manufacturer. We look at it in particular when the bid is placed. We focus on the following characteristics of available ADI in project environments: First, ADI information is uncertain, because decisions on installer and manufacturer selection have not yet been finalized. Second, information is detailed, available at the item level. We show that ADI is particularly valuable when potential demand for large projects is irregular and when proposals for potential projects have a high probability of leading to orders.     

Prevention and medication of HIV/AIDS: the case of Botswana

In this paper we developed a mathematical model which allows estimating and projecting the effects of prevention and treatment programs on the total population size, HIV-induced deaths, and life expectancies. Considering only the female population we project the changes of the demographic developments and the situation of HIV/AIDS for Botswana up to 2060. Our mathematical model is used to project the female population development considering their age-structure. Treatment programs are included through selecting a price for medication (or giving it for free). Prevention programs consist of two parts: school-based programs which try to change risky behavior and instantaneous prevention (e.g., free condoms) which has only a short-time effect on the infection risk. The main conclusions drawn from our results are that prevention-only programs always yield the fastest decrease in HIV/AIDS prevalence. Adding a medication program reduces the efficiency of the prevention interventions regarding prevalence, but it reduces the number of HIV-induced deaths and increases life expectancies. This research was partly financed by the Austrian Science Foundation (FWF) under grant No P18161-N13.     

Project Scheduling with Discounted Cash Flows and Progress Payments

In all large scale projects, there correspond cash flows that incur throughout the life of the project. The scheduling of these projects to maximize the present value of the cash flows has been a topic of recent research. The basic assumption of earlier research is that the cash flows are mainly associated with some events of the project and they occur at the event realization times. However, in several real life projects, the cash inflows do not occur at the event realization times, rather they occur at the end of some time periods, like months, as progress payments. In this article, maximizing the present value of the cash flows in such projects is considered and a mixed-integer formulation of the problem is presented. In this formulation, activity profit curves are defined and used. Computational experience on some randomly generated test problems provides promising results especially when the Benders Decomposition technique is employed for solving the problem.     

Comparative evaluation of performance of national R&D programs with heterogeneous objectives: A DEA approach

The strategic importance of performance evaluation of national R&D programs is highlighted as the resource allocation draws more attention in R&D policy agenda. Due to the heterogeneity of national R&D programs’ objectives, however, it is intractably difficult to relatively evaluate multiple programs and, consequently, few studies have been conducted on the performance comparison of the R&D programs. This study measures and compares the performance of national R&D programs using data envelopment analysis (DEA). Since DEA allows each DMU to choose the optimal weights of inputs and outputs which maximize its efficiency, it can mirror R&D programs’ unique characteristics by assigning relatively high weights to the variables in which each program has strength. Every project in every R&D program is evaluated together based on the DEA model for comparison of efficiency among different systems. Kruskal–Wallis test with a post hoc Mann–Whitney U test is then run to compare performance of R&D programs. Two alternative approaches to incorporating the importance of variables, the AR model and output integration, are also introduced. The results are expected to provide policy implications for effectively formulating and implementing national R&D programs.     

基于熵权物元的大型水利工程项目风险评价研究

大型水利工程项目是典型的复杂系统工程,为了准确预测大型水利工程风险等级,降低事故风险,论文从管理、技术、经济、政策、环境五个方面选取影响水利工程项目风险的14个指标,建立了水利工程项目风险评价指标体系.借助熵权法确定各项指标的权重,分析影响项目风险的主要因素,之后利用物元分析理论定量评价项目的风险状况.通过分析可知:跨...