Project management decisions with uncertain targets

Project management decisions with uncertain target

Moral Hazard, Incentive Contracts and Risk: Evidence from Procurement

Deadlines and penalties are widely used to incentivize effort. We model how these incentive contracts affect the work rate and time taken in a procurement setting, characterizing the efficient contract design. Using new micro-level data on Minnesota highway construction contracts that includes day-by-day information on work plans, hours actually worked and delays, we find evidence of moral hazard. As an application, we build an econometric model that endogenizes the work rate, and simulate how different incentive structures affect outcomes and the variance of contractor payments. Accounting for the traffic delays caused by construction, switching to a more efficient design would substantially increase welfare without substantially increasing the risk borne by contractors.

Scheduling access to shared space in multi-robot systems

Through this study, we introduce the idea of applying scheduling techniques to allocate spatial resources that are shared among multiple robots moving in a static environment and having temporal constraints on the arrival time to destinations. To illustrate this idea, we present an exemplified algorithm that plans and assigns a motion path to each robot. The considered problem is particularly challenging because: (i) the robots share the same environment and thus the planner must take into account overlapping paths which cannot happen at the same time; (ii) there are time deadlines thus the planner must deal with temporal constraints; (iii) new requests arrive without a priori knowledge thus the planner must be able to add new paths online and adjust old plans; (iv) the robot motion is subject to noise thus the planner must be reactive to adapt to online changes. We showcase the functioning of the proposed algorithm through a set of agent-based simulations

Project management: A Handbook of fundamentals for the packaging student and professional with a review of current literature

This thesis seeks to introduce the basic concepts and techniques of project management to packaging students and professionals. After reviewing these fundamentals, packaging students and professionals should be able to facilitate successful project management in the work place: Develop an appropriate project plan for specific objectives Understand the scheduling techniques such as work breakdown structure, Gantt Charting, PERT Charting, Network Diagramming, Assign resources and manage the project team Interpret and optimize a project plan or schedule Identify and manage project dependencies Communicate project status information appropriately and effectively Determine the impact of potential problems and make appropriate decisions for project adjustment

Human-Machine Collaborative Optimization via Apprenticeship Scheduling

Coordinating agents to complete a set of tasks with intercoupled temporal and resource constraints is computationally challenging, yet human domain experts can solve these difficult scheduling problems using paradigms learned through years of apprenticeship. A process for manually codifying this domain knowledge within a computational framework is necessary to scale beyond the ``single-expert, single-trainee" apprenticeship model. However, human domain experts often have difficulty describing their decision-making processes, causing the codification of this knowledge to become laborious. We propose a new approach for capturing domain-expert heuristics through a pairwise ranking formulation. Our approach is model-free and does not require enumerating or iterating through a large state space. We empirically demonstrate that this approach accurately learns multifaceted heuristics on a synthetic data set incorporating job-shop scheduling and vehicle routing problems, as well as on two real-world data sets consisting of demonstrations of experts solving a weapon-to-target assignment problem and a hospital resource allocation problem. We also demonstrate that policies learned from human scheduling demonstration via apprenticeship learning can substantially improve the efficiency of a branch-and-bound search for an optimal schedule. We employ this human-machine collaborative optimization technique on a variant of the weapon-to-target assignment problem. We demonstrate that this technique generates solutions substantially superior to those produced by human domain experts at a rate up to 9.5 times faster than an optimization approach and can be applied to optimally solve problems twice as complex as those solved by a human demonstrator.Comment: Portions of this paper were published in the Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) in 2016 and in the Proceedings of Robotics: Science and Systems (RSS) in 2016. The paper consists of 50 pages with 11 figures and 4 table

Workflow Scheduling Techniques and Algorithms in IaaS Cloud: A Survey

In the modern era, workflows are adopted as a powerful and attractive paradigm for expressing/solving a variety of applications like scientific, data intensive computing, and big data applications such as MapReduce and Hadoop. These complex applications are described using high-level representations in workflow methods. With the emerging model of cloud computing technology, scheduling in the cloud becomes the important research topic. Consequently, workflow scheduling problem has been studied extensively over the past few years, from homogeneous clusters, grids to the most recent paradigm, cloud computing. The challenges that need to be addressed lies in task-resource mapping, QoS requirements, resource provisioning, performance fluctuation, failure handling, resource scheduling, and data storage. This work focuses on the complete study of the resource provisioning and scheduling algorithms in cloud environment focusing on Infrastructure as a service (IaaS). We provided a comprehensive understanding of existing scheduling techniques and provided an insight into research challenges that will be a possible future direction to the researchers

Introducing risk management into the grid

Service Level Agreements (SLAs) are explicit statements about all expectations and obligations in the business partnership between customers and providers. They have been introduced in Grid computing to overcome the best effort approach, making the Grid more interesting for commercial applications. However, decisions on negotiation and system management still rely on static approaches, not reflecting the risk linked with decisions. The EC-funded project "AssessGrid" aims at introducing risk assessment and management as a novel decision paradigm into Grid computing. This paper gives a general motivation for risk management and presents the envisaged architecture of a "risk-aware" Grid middleware and Grid fabric, highlighting its functionality by means of three showcase scenarios

Decades of Delay: EPA Leadership Still Lacking in Protecting America's Great River

This report demonstrates the continuing failure of EPA's voluntary approach and the continuing and growing threats of unregulated nitrogen and phosphorus pollution. EPA has the power and the duty to act to require reasonable, common-sense regulations to address the growing scourge of nutrient pollution, and it should do so. Once again, MRC calls upon EPA to remedy this state of affairs, specifically recommending that EPA:Develop numeric phosphorus criteria for each of the eight states that have yet to adopt them, and numeric nitrogen criteria for all 10 states.Require states to assess their waters for nitrogen and phosphorus pollution and to prioritize TMDL development and implementation planning accordingly.Increase oversight of the state NPDES programs to ensure that both narrative and numeric nutrient criteria are implemented through limits in permits, including the use of Water Quality Based Effluent Limits (WQBELs) where appropriate.Disapprove TMDLs that lacking reasonable assurance that nonpoint source reductions are likely to occur and lack monitoring and timelines to ensure that planned reductions actually take place. Further, EPA needs to provide oversight to ensure consistency among EPA Regions in TMDL review and approval (especially in Regions 4 and 6.)Ensure that states' Nutrient Reduction Strategies contain implementation plans detailing point and nonpoint source reductions needed, responsible parties, funding mechanisms, milestones, measurement metrics, and reasonable timelines.Require states under Section 319 of the Clean Water Act to identify programs and practices for controlling nonpoint sources of pollution to the maximum extent possible