The document provides instructions to follow for software and server installation and implementation.
Abstract not provided.
This document provides implementation guidance for implementing personnel group FTE costs by JCA Tier 1 or 2 categories in the Contingency Contractor Optimization Tool – Engineering Prototype (CCOT-P). CCOT-P currently only allows FTE costs by personnel group to differ by mission. Changes will need to be made to the user interface inputs pages and the database
This document provides background and instructions for developing and building the Contingency Contractor Optimization Tool - Prototype (CCOT-P) application.
Sandia National Laboratories (Sandia) is in Phase 3 Sustainment of development of a prototype tool, currently referred to as the Contingency Contractor Optimization Tool - Prototype (CCOTP), under the direction of OSD Program Support. CCOT-P is intended to help provide senior Department of Defense (DoD) leaders with comprehensive insight into the global availability, readiness and capabilities of the Total Force Mix. The CCOT-P will allow senior decision makers to quickly and accurately assess the impacts, risks and mitigating strategies for proposed changes to force/capabilities assignments, apportionments and allocations options, focusing specifically on contingency contractor planning. During Phase 2 of the program, conducted during fiscal year 2012, Sandia developed an electronic storyboard prototype of the Contingency Contractor Optimization Tool that can be used for communication with senior decision makers and other Operational Contract Support (OCS) stakeholders. Phase 3 used feedback from demonstrations of the electronic storyboard prototype to develop an engineering prototype for planners to evaluate. Sandia worked with the DoD and Joint Chiefs of Staff strategic planning community to get feedback and input to ensure that the engineering prototype was developed to closely align with future planning needs. The intended deployment environment was also a key consideration as this prototype was developed. Initial release of the engineering prototype was done on servers at Sandia in the middle of Phase 3. In 2013, the tool was installed on a production pilot server managed by the OUSD(AT&L) eBusiness Center. The purpose of this document is to specify the CCOT-P engineering prototype platform requirements as of May 2016. Sandia developed the CCOT-P engineering prototype using common technologies to minimize the likelihood of deployment issues. CCOT-P engineering prototype was architected and designed to be as independent as possible of the major deployment components such as the server hardware, the server operating system, the database, and the web server. This document describes the platform requirements, the architecture, and the implementation details of the CCOT-P engineering prototype.
The Contingency Contractor Optimization Tool – Prototype (CCOT-P) database is used to store input and output data for the linear program model described in [1]. The database allows queries to retrieve this data and updating and inserting new input data.
This document describes the final software design of the Contingency Contractor Optimization Tool - Prototype. Its purpose is to provide the overall architecture of the software and the logic behind this architecture. Documentation for the individual classes is provided in the application Javadoc. The Contingency Contractor Optimization project is intended to address Department of Defense mandates by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. The Contingency Contractor Optimization Tool - Prototype was developed in Phase 3 of the OSD ATL Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for selected mission scenarios. The model optimizes the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet mission requirements as effectively as possible, based on risk, cost, and other requirements.
This requirements document serves as an addendum to the Contingency Contractor Optimization Phase 2, Requirements Document [1] and Phase 3 Requirements Document [2]. The Phase 2 Requirements document focused on the high-level requirements for the tool. The Phase 3 Requirements document provided more detailed requirements to which the engineering prototype was built in Phase 3. This document will provide detailed requirements for features and enhancements being added to the production pilot in the Phase 3 Sustainment.
The Contingency Contractor Optimization Tool - Prototype (CCOT-P) requires several third-party software packages. These are documented below for each of the CCOT-P elements: client, web server, database server, solver, web application and polling application.
The reports and test plans contained within this document serve as supporting materials to the activities listed within the “Contingency Contractor Optimization Tool – Prototype (CCOT-P) Verification & Validation Plan” [1]. The activities included test development, testing, peer reviews, and expert reviews. The engineering prototype reviews were done for both the software and the mathematical model used in CCOT-P. Section 2 includes the peer and expert review reports, which summarize the findings from each of the reviews and document the resolution of any issues. Section 3 details the test plans that were followed for functional testing of the application through the interface. Section 4 describes the unit tests that were run on the code.
This Quick Start Guide is an abbreviated version of the Contingency Contractor Optimization Phase 3, User Manual for the Contingency Contractor Optimization Tool engineering prototype. It focuses on providing quick access instructions to the core activities of the two main user roles: Planning Manager and Analyst. Based on an electronic storyboard prototype developed in Phase 2, the Contingency Contractor Optimization Tool engineering prototype was refined in Phase 3 of the OSD ATL Contingency Contractor Optimization to support strategic planning for contingency contractors. The tool uses a model to optimize the total workforce mix by minimizing the combined total costs for the selected mission scenarios. The model will optimize the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet the mission requirements as effectively as possible, based on risk, cost, and other requirements.
This User Manual provides step-by-step instructions on the Contingency Contractor Optimization Tool's major features. Activities are organized by user role. The Contingency Contractor Optimization project is intended to address former Secretary Gates' mandate in a January 2011 memo [1] and DoDI 3020.41 [2] by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. Based on an electronic storyboard prototype developed in Phase 2, the Contingency Contractor Optimization Tool engineering prototype was refined in Phase 3 of the OSD ATL Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for the selected mission scenarios. The model will optimize the match of personnel groups (military, DoD civilian, and contractors) and capabilities to meet the mission requirements as effectively as possible, based on risk, cost, and other requirements.
Abstract not provided.
This User Manual provides step-by-step instructions on the Contingency Contractor Optimization Tool's major features. Activities are organized by user role. The Contingency Contractor Optimization project is intended to address former Secretary Gates' mandate in a January 2011 memo [1] and DoDI 3020.41 [2] by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. Based on an electronic storyboard prototype developed in Phase 2, the Contingency Contractor Optimization Tool engineering prototype was refined in Phase 3 of the OSD ATL Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for the selected mission scenarios. The model will optimize the match of personnel groups (military, DoD civilian, and contractors) and capabilities to meet the mission requirements as effectively as possible, based on risk, cost, and other requirements.
This Quick Start Guide is an abbreviated version of the Contingency Contractor Optimization Phase 3, User Manual for the Contingency Contractor Optimization Tool engineering prototype. It focuses on providing quick access instructions to the core activities of the two main user roles: Planning Manager and Analyst. Based on an electronic storyboard prototype developed in Phase 2, the Contingency Contractor Optimization Tool engineering prototype was refined in Phase 3 of the OSD ATL Contingency Contractor Optimization to support strategic planning for contingency contractors. The tool uses a model to optimize the total workforce mix by minimizing the combined total costs for the selected mission scenarios. The model will optimize the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet the mission requirements as effectively as possible, based on risk, cost, and other requirements.
The goal of Phase 3 the OSD ATL Contingency Contractor Optimization (CCO) project is to create an engineering prototype of a tool for the contingency contractor element of total force planning during the Support for Strategic Analysis (SSA). An optimization model was developed to determine the optimal mix of military, Department of Defense (DoD) civilians, and contractors that accomplishes a set of user defined mission requirements at the lowest possible cost while honoring resource limitations and manpower use rules. An additional feature allows the model to understand the variability of the Total Force Mix when there is uncertainty in mission requirements.
When developing linear programming models, issues such as budget limitations, customer requirements, or licensing may preclude the use of commercial linear programming solvers. In such cases, one option is to use an open-source linear programming solver. A survey of linear programming tools was conducted to identify potential open-source solvers. From this survey, four open-source solvers were tested using a collection of linear programming test problems and the results were compared to IBM ILOG CPLEX Optimizer (CPLEX) [1], an industry standard. The solvers considered were: COIN-OR Linear Programming (CLP) [2], [3], GNU Linear Programming Kit (GLPK) [4], lp_solve [5] and Modular In-core Nonlinear Optimization System (MINOS) [6]. As no open-source solver outperforms CPLEX, this study demonstrates the power of commercial linear programming software. CLP was found to be the top performing open-source solver considered in terms of capability and speed. GLPK also performed well but cannot match the speed of CLP or CPLEX. lp_solve and MINOS were considerably slower and encountered issues when solving several test problems.
Abstract not provided.
The goal of Phase 3 the OSD ATL Contingency Contractor Optimization (CCO) project is to create an engineering prototype of a tool for the contingency contractor element of total force planning during the Support for Strategic Analysis (SSA). An optimization model was developed to determine the optimal mix of military, Department of Defense (DoD) civilians, and contractors that accomplishes a set of user defined mission requirements at the lowest possible cost while honoring resource limitations and manpower use rules. An additional feature allows the model to understand the variability of the Total Force Mix when there is uncertainty in mission requirements.