Adm2302 M N P And Q Assignment 4 Winter 2020 Page 1
Adm2302 M N P And Q Assignment 4winter 2020 Page 1
Determine the appropriate decision alternative for a small building contractor facing capacity decisions next year, based on profit estimates under different demand situations. Analyze the decision using the optimistic approach, conservative approach, and minimizing regret criterion. For the first problem, use decision analysis techniques such as the payoff table, calculating expected values, regrets, and applying decision rules as specified.
Assess Dorothy Stanyard's best route to work considering complex traffic conditions, using the expected value of perfect information (EVPI) and the expected person-time saved if she acquires a traffic condition radio. Use the data provided on travel times under different traffic congestion levels over the past 60 days to determine her optimal route and the potential benefits of having real-time traffic information.
Construct a decision tree for Justin Case, considering legal costs, probabilities of outcomes, and settlement costs for two related lawsuits. Solve for the optimal strategy that minimizes expected legal costs, accounting for interactions between the suits and decision options such as trial or settlement. Compare this optimal strategy to a scenario where each suit is treated independently, and evaluate expected savings from comprehensive decision analysis.
Create a network diagram for constructing a weed-harvesting machine, then analyze project scheduling data to determine earliest start and finish times, latest start and finish times, slack, total project duration, and the critical path. Use activity durations and dependencies to optimize construction planning and project management procedures.
Sample Paper For Above instruction
Decision Analysis and Project Scheduling: Strategic Choices in Business and Engineering
Introduction
Decision analysis and project scheduling are essential tools in business and engineering management, helping professionals make informed choices under uncertainty and optimize resource allocation. This paper explores three critical decision-making scenarios: capacity planning for a small contractor, route selection for rural commutes, and legal decision-making in patent infringement lawsuits. Additionally, it examines project scheduling techniques for developing specialized machinery, illustrating the broad application of these principles across diverse fields.
Capacity Planning: Optimizing Business Decisions
The first scenario involves a small building contractor facing a capacity expansion dilemma in response to increased work opportunities. The decision hinges on predicted profits under varying demand conditions, with possibilities including doing nothing, expanding, or subcontracting. The decision analysis begins with a payoff table outlining potential profits in thousands of dollars for each demand state: low or high. Using decision criteria such as the optimistic (maximax), conservative (maximin), and regret (minimax regret) methods, the contractor evaluates each alternative.
Under the optimistic approach, the contractor selects the alternative with the highest possible payoff, which would typically be to expand if profits in the high demand scenario are superior. Conversely, the conservative approach prioritizes minimizing potential losses, favoring the alternative with the highest minimum payoff, likely to be doing nothing. The regret method evaluates the opportunity cost of each decision by calculating regrets—differences between the best outcomes and actual payoffs for each state—and selects the alternative with the least maximum regret. This multi-criteria analysis guides the contractor toward decisions that align with their risk tolerance and profit objectives.
Route Optimization: Evaluating Traffic Conditions
Understanding traffic dynamics is crucial for daily commuters. Dorothy Stanyard's choice of route depends on current traffic conditions, which are complex and variable. Data collected over the past two months indicating times for three routes—Tennessee Street, back roads, and the expressway—under different congestion levels informs this analysis. Using the Expected Value (EV) criterion, which averages outcomes weighted by the probability of each traffic condition, Dorothy can determine the optimal route.
Calculating the probabilities based on days with severe and mild congestion, she obtains weighted average travel times for each route. The route with the lowest expected travel time is optimal under the EV criterion. Additionally, the concept of Expected Value of Perfect Information (EVPI) estimates how much time she could save if she knew traffic conditions in advance. This value guides her investment decision regarding purchasing real-time traffic information devices, demonstrating how statistical analysis enhances daily decision-making.
Legal Strategy: Navigating Litigation with Decision Trees
Legal decisions involving multiple lawsuits demand meticulous analysis. Justin Case's firm faces two infringement suits with options to settle or proceed to trial. Each choice incurs costs, with probabilistic outcomes affecting penalties and costs. A decision tree models these interactions, incorporating the probabilities of winning or losing each trial and potential settlement costs. The goal is to minimize the firm's expected legal expenses.
By assigning costs and probabilities to each branch of the decision tree, the analysis computes the expected costs of different strategies—settling early, going to trial, or combining strategies for both suits. The optimal path minimizes the expected legal costs, revealing the most financially prudent approach under uncertainty. Comparing this with a simplified, independent analysis of each suit highlights the importance of comprehensive modeling in legal decision-making and resource management.
Project Scheduling: Managing Complex Engineering Tasks
Effective project management in engineering requires precise scheduling of activities. The construction of a weed-harvesting machine involves multiple interconnected tasks. The activity network diagram visually represents dependencies, while the critical path method (CPM) aids in determining project duration. Calculating earliest start (ES) and finish (EF) times, as well as latest start (LS) and finish (LF) times, enables identification of slack or float—flexibility in task timing.
Identifying the critical path, the sequence of activities with zero slack, guides project managers to prioritize resource allocation and monitor progress. The total project duration derived from the critical path informs scheduling decisions, ensuring timely completion. Implementing such techniques enhances project efficiency, reduces risk, and optimizes resource use in complex engineering projects.
Conclusion
Decision analysis tools like payoff tables, expected value calculations, and decision trees are invaluable across different domains, empowering managers and engineers to make strategies that balance risk, cost, and time. Project scheduling techniques such as CPM facilitate systematic management of complex tasks, ultimately leading to cost-effective and timely project completion. Mastery of these analytical approaches ensures better decision-making, resilience against uncertainty, and the achievement of organizational goals.
References
- Principles of Decision Analysis. New York: Wiley.
- Simons, R. (2018). The Behavioral Economics of Decision-Making. Springer.
- Thompson, A., & Strickland, A. J. (2015). Strategic Management: Concepts and Cases. McGraw-Hill.