AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Application of expert systems in project management decision aiding

The feasibility of developing an expert systems-based project management decision aid to enhance the performance of NASA project managers was assessed. The research effort included extensive literature reviews in the areas of project management, project management decision aiding, expert systems technology, and human-computer interface engineering. Literature reviews were augmented by focused interviews with NASA managers. Time estimation for project scheduling was identified as the target activity for decision augmentation, and a design was developed for an Integrated NASA System for Intelligent Time Estimation (INSITE). The proposed INSITE design was judged feasible with a low level of risk. A partial proof-of-concept experiment was performed and was successful. Specific conclusions drawn from the research and analyses are included. The INSITE concept is potentially applicable in any management sphere, commercial or government, where time estimation is required for project scheduling. As project scheduling is a nearly universal management activity, the range of possibilities is considerable. The INSITE concept also holds potential for enhancing other management tasks, especially in areas such as cost estimation, where estimation-by-analogy is already a proven method

Integrated engineering environments for large complex products

An introduction is given to the Engineering Design Centre at the University of Newcastle upon Tyne, along with a brief explanation of the main focus towards large made-to-order products. Three key areas of research at the Centre, which have evolved as a result of collaboration with industrial partners from various sectors of industry, are identified as (1) decision support and optimisation, (2) design for lifecycle, and (3) design integration and co-ordination. A summary of the unique features of large made-to-order products is then presented, which includes the need for integration and co-ordination technologies. Thus, an overview of the existing integration and co-ordination technologies is presented followed by a brief explanation of research in these areas at the Engineering Design Centre. A more detailed description is then presented regarding the co-ordination aspect of research being conducted at the Engineering Design Centre, in collaboration with the CAD Centre at the University of Strathclyde. Concurrent Engineering is acknowledged as a strategy for improving the design process, however design coordination is viewed as a principal requirement for its successful implementation. That is, design co-ordination is proposed as being the key to a mechanism that is able to maximise and realise any potential opportunity of concurrency. Thus, an agentoriented approach to co-ordination is presented, which incorporates various types of agents responsible for managing their respective activities. The co-ordinated approach, which is implemented within the Design Co-ordination System, includes features such as resource management and monitoring, dynamic scheduling, activity direction, task enactment, and information management. An application of the Design Co-ordination System, in conjunction with a robust concept exploration tool, shows that the computational design analysis involved in evaluating many design concepts can be performed more efficiently through a co-ordinated approach

Strengthening Construction Management in the Rural Rehab Line of Business

The Five Key ObservationsObservation#1: Rural rehab success emanated from positive thinking and persistent implementationObservation #2: Almost every RHRO would benefit from a substantial increase in the per unit funding available, especially in light of the forthcoming HUD HOME requirement to establish written rehab standards in ten subcategories.Observation #3: A smartphone and tablet with 20 to 40 apps is the rehab specialist's Swiss Army knife. They are our, GPS, calculator, spec writer, office lifeline in case of danger, camera, clock, cost estimator calendar and a hundred other single-purpose but very important uses.Observation #4: NeighborWorks® Rural Initiative could provide a clearinghouse for success techniques targeted to rural rehab. Each month it might focus on a specific aspect of rehab management; inspection checklists in January, green specs in February, feasibility checklist in March, contractor qualification questionnaires in April and so on.Observation #5: Even with most components of in-house contractor success formula in place, per the Statistic Research Institute 53% of construction firms go out of business with in the first 4 years. It remains a very risky model that requires significant; funding, staff experience, administrative support and risk tolerance.Three Rehab Production Models And Their AlternativesThis middle section restates the introduction and methodology and offers a detailed review of the Traditional Rehab Specialist, Construction Management Of Subcontractor and the In-House General Contractor production models .for each model the article provides: definition and staffing pattern, design roles and tasks for each major player, benefits and challenges, alternative models and finally recommendations for successful implementationFocus TopicsDuring our interview process, three ideas surfaced that were best served with a mini discussion of the topic rather than being embedded in the already large middle section.The three topics are; software and technology, management of community relations – marketing and quality control, and budget solution

Two Timescale Convergent Q-learning for Sleep--Scheduling in Wireless Sensor Networks

In this paper, we consider an intrusion detection application for Wireless Sensor Networks (WSNs). We study the problem of scheduling the sleep times of the individual sensors to maximize the network lifetime while keeping the tracking error to a minimum. We formulate this problem as a partially-observable Markov decision process (POMDP) with continuous state-action spaces, in a manner similar to (Fuemmeler and Veeravalli [2008]). However, unlike their formulation, we consider infinite horizon discounted and average cost objectives as performance criteria. For each criterion, we propose a convergent on-policy Q-learning algorithm that operates on two timescales, while employing function approximation to handle the curse of dimensionality associated with the underlying POMDP. Our proposed algorithm incorporates a policy gradient update using a one-simulation simultaneous perturbation stochastic approximation (SPSA) estimate on the faster timescale, while the Q-value parameter (arising from a linear function approximation for the Q-values) is updated in an on-policy temporal difference (TD) algorithm-like fashion on the slower timescale. The feature selection scheme employed in each of our algorithms manages the energy and tracking components in a manner that assists the search for the optimal sleep-scheduling policy. For the sake of comparison, in both discounted and average settings, we also develop a function approximation analogue of the Q-learning algorithm. This algorithm, unlike the two-timescale variant, does not possess theoretical convergence guarantees. Finally, we also adapt our algorithms to include a stochastic iterative estimation scheme for the intruder's mobility model. Our simulation results on a 2-dimensional network setting suggest that our algorithms result in better tracking accuracy at the cost of only a few additional sensors, in comparison to a recent prior work

A Case Study in Optimization of Resource Distribution to Cope with Unanticipated Changes in Requirements

It is a known fact that requirements change continuously, and as a consequence, it may be necessary to reschedule development activities so that the new requirements can be addressed in a costeffective manner. Unfortunately, changes in requirements cannot be specified precisely. Moreover, current software development methods do not provide explicit means to adapt development processes with respect to unanticipated changes in requirements. This article first proposes a method based on Markov Decision Theory, which determines the estimated optimal development schedule with respect to probabilistic product demands and resource constraints. Second, a tool is described that is built to support the method. Finally, some experimental results are presented on the applicability of the proposed method

New Completeness Methods for Estimating Exoplanet Discoveries by Direct Detection

We report new methods for evaluating realistic observing programs that search stars for planets by direct imaging, where observations are selected from an optimized star list, and where stars can be observed multiple times. We show how these methods bring critical insight into the design of the mission & its instruments. These methods provide an estimate of the outcome of the observing program: the probability distribution of discoveries (detection and/or characterization), & an estimate of the occurrence rate of planets (eta). We show that these parameters can be accurately estimated from a single mission simulation, without the need for a complete Monte Carlo mission simulation, & we prove the accuracy of this new approach. Our methods provide the tools to define a mission for a particular science goal, for example defined by the expected number of discoveries and its confidence level. We detail how an optimized star list can be built & how successive observations can be selected. Our approach also provides other critical mission attributes, such as the number of stars expected to be searched, & the probability of zero discoveries. Because these attributes depend strongly on the mission scale, our methods are directly applicable to the design of such future missions & provide guidance to the mission & instrument design based on scientific performance. We illustrate our new methods with practical calculations & exploratory design reference missions for JWST operating with a distant starshade to reduce scattered and diffracted starlight on the focal plane. We estimate that 5 habitable Earth-mass planets would be discovered & characterized with spectroscopy, with a probability of 0 discoveries of 0.004, assuming a small fraction of JWST observing time (7%), eta=0.3, and 70 observing visits, limited by starshade fuel.Comment: 27 pages, 4 figures, 6 tables, accepted for publication by Ap