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It typically describes the project in enough detail to let potential offerors determine if they wish to compete and forms the basis for requesting qualifications submissions from which the most highly qualified offerors can be identified. Fixed price/best design means a form of best value selection in which contract price is established by the owner and stated in the Request for Proposals document. Design solutions and other qualitative factors are evaluated and rated, with award going to the firm offering the best qualitative proposal for the established price. Communications are exchanges, between the contracting agency and offerors, after receipt of proposals, which lead to the establishment of the competitive range. The experiments are carried out on a 2.50 GHz 11th Gen Intel(R) Core(TM) i7-11,700 CPU with 16 GB memory and 64-bit Windows11 operating system using Matlab R2021a. In order to verify the performance of MCOA algorithm, MCOA is compared with nine metaheuristic algorithms in this subsection.
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In the d-dimensional optimization problem of COA, each crayfish is a 1 × d matrix representing the solution of the problem. In a set of variables (X1, X2, X3…… Xd), the position (X) of each crayfish is between the upper boundary (ub) and lower boundary (lb) of the search space. In each evaluation of the algorithm, an optimal solution is calculated, and the solutions calculated in each evaluation are compared, and the optimal solution is found and stored as the optimal solution of the whole problem.
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According to the comparison results with the original algorithm, it is proved that MCOA algorithm has a good improvement effect. However, in most of the remaining functions, the significance level of MCOA compared with the other nine algorithms is less than 5%, which is a significant difference. Among them, each crayfish has a certain difference in its own perception of water environment r, X2 is a random position between the candidate optimal position and the current position, which is calculated by Eq.
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These results demonstrate that MCOA exhibits robust optimization performance and high stability in solving high-dimensional feature selection problems. Moreover, MCOA outperforms COA, showcasing its superior improvement in solving these complex problems. Filter methods, being relatively single and one-sided, approach the problem of feature selection in a straightforward manner by considering individual features and their relationships within the dataset. However, they might lack the flexibility needed for complex and specific problem scenarios. However, wrapper methods offer tailored and problem-specific solutions.
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Risk should be allocated with consideration given to the party who is in the best position to manage and control a given risk or the impact of a given risk. (9) The design-build contract must include termination provisions in the event that the no-build alternative is selected. Weakness means a flaw in the proposal that increases the risk of unsuccessful contract performance. A significant weakness in the proposal is a flaw that appreciably increases the risk of unsuccessful contract performance.
2 Ghost opposition-based learning strategy
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MCOA introduces an environmental update mechanism inspired by crayfish's preference for living in fresh flowing water. MCOA incorporates crayfish's innate perception abilities to assess the quality of the surrounding aquatic environment, determining whether the current habitat is suitable for survival. It heightens the randomness within the group, widens the search scope for crayfish, enhances the algorithm's exploration efficiency, and effectively strengthens the algorithm’s global optimization capabilities. Additionally, the ghost opposition-based learning strategy (Jia et al. 2023c) is implemented to introduce random population initialization when the algorithm becomes trapped in local optima. This enhancement significantly improves the algorithm's capability to escape local optima, promoting better exploration of the solution space. After the careful integration of the aforementioned two strategies, the search efficiency and predation speed of the crayfish algorithm experience a substantial improvement.
Modified crayfish optimization algorithm (MCOA)
Actual construction timelines will vary as well and you will need to work with a contractor, builder or other professional to estimate this phase of your project. The average timeline for a single room Modsy Renovation Design service project is about 5-6 weeks from beginning (kickoff call) to end (design finalization). Project timelines will vary depending on your project’s scale, complexity and communication preferences. CAD drawings are the most expensive option, but offer the most flexibility if you have major changes to make to the home.
At your discretion, you may elect to pay a stipend to unsuccessful offerors who have submitted responsive proposals. The decision to do so should be based on your analysis of the estimated proposal development costs and the anticipated degree of competition during the procurement process. (c) The contracting agency must receive prior FHWA concurrence before issuing the RFP, awarding a design-build contract and proceeding with preliminary design work under the design-build contract.
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In addition, we will also introduce the high-dimensional feature selection problem of the wrapper method, and further judge whether MCOA has good optimization performance and the ability to deal with diversified problems through the classification and processing effect of data. Moreover, MCOA’s practical applicability is demonstrated through applications to four constrained engineering problems and high-dimensional feature selection challenges. These experiments underscore MCOA’s efficacy in real-world scenarios, but MCOA can only solve the optimization problem of a single goal. In future studies, efforts will be made to further optimize MCOA and enhance its function. We will exploitation multi-objective version of the algorithm to increase the search ability and convergence of the algorithm through non-dominated sorting, multi-objective selection, crossover and mutation, etc., to solve more complex practical problems.
Crayfish Optimization Algorithm (COA) is innovative and easy to implement, but the crayfish search efficiency decreases in the later stage of the algorithm, and the algorithm is easy to fall into local optimum. To solve these problems, this paper proposes an modified crayfish optimization algorithm (MCOA). Based on the survival habits of crayfish, MCOA proposes an environmental renewal mechanism that uses water quality factors to guide crayfish to seek a better environment. In addition, integrating a learning strategy based on ghost antagonism into MCOA enhances its ability to evade local optimality. To evaluate the performance of MCOA, tests were performed using the IEEE CEC2020 benchmark function and experiments were conducted using four constraint engineering problems and feature selection problems.
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(6) Allow a design-builder to proceed with final design and construction for any projects, or portions thereof, for which the NEPA process has been completed. Single-phase selection process means a procurement process where price and/or technical proposals are submitted in response to an RFP. Prequalification means the contracting agency's process for determining whether a firm is fundamentally qualified to compete for a certain project or class of projects. The prequalification process may be based on financial, management and other types of qualitative data. Modified design-build means a variation of design-build in which the contracting agency furnishes offerors with partially complete plans.
Moreover, the algorithm's convergence rate and global optimization ability are significantly enhanced, leading to more effective and efficient problem-solving capabilities. The Crayfish Optimization Algorithm (COA) is grounded in swarm intelligence, drawing inspiration from crayfish behavior to find optimal solutions within a specific range. However, COA’s limitations stem from neglecting crucial survival traits of crayfish, such as crawling against water to discover better aquatic environments.
The owner should award the contract to the apparent successful offeror unless an organizational conflict of interest is determined to exist that cannot be avoided, neutralized, or mitigated. Design-builder means the entity contractually responsible for delivering the project design and construction. Deficiency means a material failure of a proposal to meet a contracting agency requirement or a combination of significant weaknesses in a proposal that increases the risk of unsuccessful contract performance to an unacceptable level.
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