An adjustable robust optimization model for the resource-constrained project scheduling problem with uncertain activity durations

This paper addresses the resource-constrained project scheduling problem with uncertain activity durations. An adaptive robust optimization model is proposed to derive the resource allocation decisions that minimize the worst-case makespan, under general polyhedral uncertainty sets. The properties of the model are analyzed, assuming that the activity durations are subject to interval uncertainty where the level of robustness is controlled by a protection factor related to the risk aversion of the decision maker. A general decomposition approach is proposed to solve the robust counterpart of the resource-constrained project scheduling problem, further tailored to address the uncertainty set with the protection factor. An extensive computational study is presented on benchmark instances adapted from the PSPLIB.     

Evaluation of simple dispatching rules for dynamic single-machine earliness/tardiness problem

Abstract. This paper investigates the effects of four simple dispatching rules on just-in-time production related performance measures of mean and maximum absolute lateness. The rules used are modified due date (MDD), shortest processing time (SPT), earliest due date (EDD), and first in first out (FIFO). A single machine is used under three utilization levels. Due-dates are set according to total work content rule. The results indicate that each rule performs well under certain conditions. The MDD rule is the best one to minimize mean absolute lateness. The EDD and FIFO rules do well in minimizing the maximum absolute lateness. Economic interpretation of these performance measures are also discussed.     

A comparative study of some priority dispatching rules under different shop loads

Priority dispatching rules and shop load affect job-shop performance. This paper evaluates ten different priority dispatching rules with respect to six different performance criteria under light, medium and heavy shop loads. Simulation was used as a tool to determine the rankings of the dispatching rules for a given shop load and performance criteria. A comparative study was conducted to investigate the performance of these rules. Two rules, ‘shortest processing time” and ‘least work remaining’, performed well under criteria related to the processing time. It was found that the rules that perform well in average and r.m.s. tardiness perform poorly under percentage-of-jobs-late criterion. The experimental results are conveyed with critical comments on the performance of the dispatching rules under different loading conditions of the shop.     

A hybrid knowledge discovery model using decision tree and neural network for selecting dispatching rules of a semiconductor final testing factory

One of the most challenging production decisions in the semiconductor testing industry is to select the most appropriate dispatching rule which can be employed on the shop floor to achieve high manufacturing performance against a changing environment. Job dispatching in the semiconductor final testing industry is severely constrained by many resources conflicts and has to fulfil a changing performance required by customers and plant managers. In this study we have developed a hybrid knowledge discovery model, using a combination of a decision tree and a back-propagation neural network, to determine an appropriate dispatching rule using production data with noise information, and to predict its performance. We built an object-oriented simulation model to mimic shop floor activities of a semiconductor testing plant and collected system status and resultant performances of several typical dispatching rules, earliest-due-date (EDD) rule, first-come-first-served rule, and a practical dispatching heuristic taking set-up reduction into consideration. Performances such as work-in-process, set-up overhead, completion time, and tardiness are examined. Experiments have shown that the proposed decision tree found the most suitable dispatching rule given a specific performance measure and system status, and the back propagation neural network then predicted precisely the performance of the selected rule.     

A cross-national comparison of public project benefits management practices – the effectiveness of benefits management frameworks in application

Abstract

Benefits are the principal reason why an organization may seek to enact change through programmes and projects. The discipline of identification, definition, planning, tracking and realization of benefits is recognized to be instrumental in achieving organizational strategy. In this study, we describe the results of a cross-national comparison of public sector benefits management (BM) practices in Australia, Canada, the UK and the USA. It explores ‘BM practices in action’, considering to what extent ‘espoused’ or ‘mandated’ frameworks are actually practised and perceived by their users. Employing qualitative analysis, semi-structured interview data were analysed from 46 participants with experience in sponsoring, managing and/or reviewing government projects. The results expose considerable variation in the adoption and standardization of BM frameworks from inter and intragovernmental perspectives. We evidence a strong focus on benefits identification across the data set, specifically at the outset (the business case stage seeking project approval) and observe deterioration in focus as the project or programme progresses through the authorization (or assurance) approval gates towards close-out and operations. The results further emphasize the prominence of political interest, leadership buy-in, a benefits-driven culture and a transparent benefits reporting mechanism in the implementation of ‘effective’ BM frameworks.     

Integration of project management,human resource development,and business teams: a partnership,planning model for organizational training and development initiatives

The changing business environment has challenged organizations to explore unique ways to ensure the success of online training initiatives. Thus, project teams, including training managers, should not only support organizational training and development initiatives; but, they also need to use project-focused, planning models for implementation. This paper proposes a model that is an extension of the model for business and training partnership developed by Price. The proposed model includes the integration of project management, human resource development (HRD), and business teams in order to enhance the success of training implementations through a sequential, planned framework. The model includes phases, best practices, and supporting tools to assist in managing and administering training and development projects. The approach developed in this research includes an account of the activities associated with initiating, planning, executing, monitoring and controlling, and closing processes for an online training initiative conducted in an oil and gas organization. This research also discusses implications of the proposed model for HRD professionals, because they are typically the champion of training and development initiatives within organizations today.     

工程项目采购管理的MBHN分析技术及应用

企业如何确定工程项目的采购集成部分,是项目管理规划阶段重要基础工作。MBHN分析技术是一项分析确定工程项目需要采购部分的工具,通过对企业有无制造资格和自制还是采购的二维分析,企业可以清晰地划分确定该工程项目自制部分和采购集成部分。应用实例说明了MBHN分析技术可行性和有效性。     

Incentive Contracts for Managing a Project with Uncertain Completion Time

We examine two time‐related incentive project management contracts (C1 and C2 contracts) when the manager conducts a reverse auction. Under the C1 contract, the contractor with the lowest bid price wins; however, the manager imposes a linear and symmetric incentive/disincentive for early/late completion according to a pre‐specified due date. Under the C2 contract, the winning contractor has the lowest composite score that is based on the quoted price and the quoted due date; however, in addition to the linear and symmetric penalty/incentive, the contractor is subject to an additional penalty for late completion. While the C2 contract is more sophisticated than the C1 contract (in terms of the number of decisions that each party has to make), our analysis reveals that, unless the project is truly urgent, the more complicated C2 contract adds no value to the manager— the simple C1 contract will suffice.     

基于研究领域匹配度的科研项目评审指派方法

针对科研项目评审中的项目指派问题,提出了一种基于研究领域匹配度的指派方法。首先给出了项目与评审专家研究领域匹配度的度量模型。在此基础上,考虑项目与评审专家研究领域的匹配情况,构建了将项目指派给不同评审专家的决策模型,并给出了模型的求解方法,最后通过算例说明了方法的可行性。     

Applying a fuzzy analytic network process to construct a purchase project. A case for the purchase of a slicing diamond cutting machine

In this paper we propose a fuzzy extension of the analytic network process (ANP) that uses uncertain human preferences as input information in the project evaluation of precision diamond cutting machines. The resulting fuzzy ANP enhances the potential of the ANP for dealing with imprecise and uncertain human comparison judgments. It allows for multiple representations of uncertain human preferences, as crisp, interval, and fuzzy judgments and can find a solution from incomplete sets of pair-wise comparisons. An important feature of the proposed method is that it measures the inconsistency of the uncertain human preferences by an appropriate consistency index. Simultaneously, process capability indices are presented to demonstrate and verify the feasibility and effectiveness of the proposed methods. In the future, the proposal can provide the best way to control and calculate effective purchasing of diamond cutting machines for wafer slicing by project buyers. This purchasing project will save cost and ease the case of purchase.     

The use of performance measurement as a basis for project control of offshore modification oil and gas projects

The methods presented in this article are based on the qualitative and quantitative analysis of close-out data drawn from a portfolio of 38 modification projects. The primary premise is that modification projects are intrinsically subject to quantity and complexity growth during the course of detailed engineering as a consequence of the indeterminate interface with the existing facility. The normative project control routines need to be supplemented by material take-offs-based weight monitoring as a basis for re-estimation and re-calibration of the project baselines as detailed engineering proceeds in order to mitigate this uncertainty as early as possible. Similarly, estimating needs to be based on norms drawn from performance measurement of modification work rather than extrapolations from greenfield projects, particularly the work performed on the platforms. This article presents a portfolio of project control methods based on the performance measurement principle covering the short term of single projects as well as the longer term multi-project perspective.     

A Structural model for the impact of supply chain relationship traits on project performance in construction

The objectives of this study are to discover the supply chain relationship traits in construction and their impact on the project performance. Using factor analysis technique, the supply chain relationship traits were determined to be collaboration in the supply chain, support and commitment to the supply chain, and sharing the benefits and risks. A two-step SEM model was then established to test the hypothesised relationship between the supply chain relationship traits and the project performance. The findings indicated that the supply chain relationship traits have a significant positive impact on the project performance. This study contributes to the body of knowledge relating to the construction supply chain management. The findings may help the parties to identify the attributes that may improve the relationships among them and result in better project performance.     

Outsourcing vs. in-house production: a comparison of supply chain contracts with effort dependent demand

We analyze the effort and pricing decisions in a two facility supply chain in which one of the parties can exert costly effort to increase demand. We consider an outsourcing model in which the supplier makes the effort decision and an in-house production model in which the manufacturer decides on the effort level and we compare these two models with each other. We analyze and compare several contracts for decentralized supply chain models and we aim to find which contracts are best to use in different cases. We find the optimal contract parameters in each case and perform extensive computational testing to compare the efficiencies of these contracts. We also analyze the effect of the powers of the parties in the system and the effect of system parameters on the performances of the contracts and on the optimal values of the model variables such as price, effort and demand.     

Engineering of a decision support system for underground coal mine planning and production scheduling

This paper reports on the development of a computer-based management information system at Datong Coal Company, the largest subsidiary of China National Coal Corporation. Particularly presented is the development methodology of a decision support system for underground coal mine planning and production scheduling, including an integration of computer graphics, database management, mathematical modelling and knowledge engineering techniques and a coupling of life cycle and prototyping software engineering processes to support systems quality assurance.     

A comparative analysis of due date based job sequencing rules in a flow shop with multiple processors

The literature on job scheduling recognizes the importance of due date performance criteria such as mean tardiness and maximum tardiness. A number of studies test a large number of sequencing rules for these criteria in job shop and flow shop settings. The object of this present research is to examine the performance of some well-known priority rules in a flow shop with multiple processors. This study investigates the performance of ten priority rules in terms of mean and maximum tardiness. It examines the effects of problem characteristics, such as number of jobs, number of machines stages and number of parallel processors at each stage, and the performance of priority rules using regression analysis. The findings of the study suggest that the primary determinants of tardiness-based criteria are problem characteristics. In addition, both the regression analysis and the analysis of variance provide strong evidence of the strategy-effect. Finally, a detailed performance review of examined priority rules for various problem characteristics is presented.     

A systematic approach for supply chain conflict detection with a hierarchical Petri Net extension

Coordinating and managing distributed entities in a supply chain is a challenging task due, in part, to conflicts present in such systems. If not handled effectively, the conflict can degrade the performance of the system as a whole due to the fact that each individual entity may be working towards goals that sub-optimize the integrated system. Therefore, the ability to discover conflicts would be a valuable asset, particularly if the discovery occurred proactively. This paper presents a methodology, extending the concept of basic Petri Nets, to discover supply chain conflict before they occur and cause detrimental effects to system performance. The approach involves linking hierarchical levels of the supply chain system and detecting conflicts occurring when the single entities, each optimized for it own operations, are combined together in a supply chain. These conflicts are not obvious or intuitive in examining the single entities of the supply chain, but when integrated the conflicts are discovered by the methodology. We applied the proposed methodology on a real-world supply chain to illustrate the validity of the tool. Although, further research is needed to fully explore this method of conflict detection, we believe that this research does indeed provide some much needed insight into the daunting task of conflict discovery and therefore proactive handling of these potentially negative occurrences in the supply chain.     

A stochastic programming model for production planning of perishable products with postponement

This study addresses the production planning problem for perishable products, in which the cost and shortage of products are minimised subject to a set of constraints such as warehouse space, labour working time and machine time. Using the concept of postponement, the production process for perishable products is differentiated into two phases to better utilise the resources. A two-stage stochastic programming with recourse model is developed to determine the production loading plan with uncertain demand and parameters. A set of data from a toy company shows the benefits of the postponement strategy: these include lower total cost and higher utilisation of resources. The impact of unit shortage cost under different probability distribution of economic scenarios on the total cost is analyzed. Comparative analysis of solutions with and without postponement strategies is also performed.     

Adaptive Management: A Paradigm for Remediation of Public Facilities Following a Terrorist Attack

Terrorist actions are aimed at maximizing harm (health, psychological, economical, and political) through the combined physical impacts of the act and fear. Immediate and effective response to a terrorist act is critical to limit human and environmental harm, effectively restore facility function, and maintain public confidence. Though there have been terrorist attacks in public facilities that we have learned from, overall our experiences in restoration of public facilities following a terrorist attack are limited. Restoration of public facilities following a release of a hazardous material is inherently far more complex than in industrial settings and has many unique technical, economic, social, and political challenges. For example, there may be a great need to quickly restore the facility to full operation and allow public access even though it was not designed for easy or rapid restoration, and critical information is needed for quantitative risk assessment and effective restoration must be anticipated to be incomplete and uncertain. Whereas present planning documents have substantial linearity in their organization, the “adaptive management” paradigm provides a constructive parallel paradigm for restoration of public facilities that anticipates and plans for uncertainty, inefficiencies, and stakeholder participation. Adaptive management grew out of the need to manage and restore natural resources in highly complex and changing environments with limited knowledge about causal relationships and responses to restoration actions. Similarities between natural resource management and restoration of a public facility after a terrorist attack suggest that integration of adaptive management principles explicitly into restoration processes will result in substantially enhanced and flexible responses necessary to meet the uncertainties of potential terrorist attacks.     

A Multi‐Supplier Sourcing Problem with a Preference Ordering of Suppliers

We study a sourcing problem faced by a firm that seeks to procure a product or a component from a pool of alternative suppliers. The firm has a preference ordering of the suppliers based on factors such as their past performance, quality, service, geographical location, and financial strength, which are commonly included in a supplier scorecard system. Thus, the firm first uses available inventory from supplier 1, if any, then supplier 2, if any, and so on. The suppliers differ in costs and prices. The buyer firm seeks to determine which suppliers to purchase from and in what quantities to maximize its total expected profit subject to the preference ordering constraint. We present the optimal solution to this problem, and show that it has a portfolio structure. It consists of a sub‐set of suppliers that are ordered by their underage and overage costs. This portfolio achieves a substantial profit gain compared to sourcing from a unique supplier. We present an efficient algorithm to compute the optimal solution. Our model applies to component sourcing problems in manufacturing, merchandizing problems in retailing, and capacity reservation problems in services.