Application Of Multi-objective Optimization Method Research Articles

ПІДВИЩЕННЯ ЕФЕКТИВНОСТІ БУДІВЕЛЬНИХ ПРОЄКТІВ ЗАВДЯКИ ОПТИМІЗОВАНИМ ЛОГІСТИЧНИМ РІШЕННЯМ

This article provides an overview of the importance of efficient logistics solutions in construction projects and explores strategies to enhance project performance. It examines key areas such as streamlining material procurement and implementing just-in-time delivery practices to improve cost-efficiency and minimize delays. The article offers insights and recommendations for optimizing logistics operations in the construction industry. The publication focuses on the importance and prospects of efficient logistics management in the construction process and explores the application of multi-objective optimization methods to achieve sustainable results. The research highlights the challenges associated with logistics in the context of construction and emphasizes the need for a comprehensive approach to addressing them. By employing multi-objective optimization methods, the article proposes strategies for optimizing logistics operations, such as transportation, inventory management, and supply chain coordination. The study aims to provide valuable insights and practical recommendations to enhance efficiency in implementing construction projects. The conclusions of this research contribute to expanding knowledge in the field of logistics management and offer valuable recommendations for further practices in building supply chains during construction and reconstruction projects.

Application of multiobjective optimization methods for solving of a ship design problem

In the present paper we demonstrate the application of single-objective and multi-objective optimization methods for solving the problem of ship design characteristics optimization. The impact analysis of local criteria on the values of design characteristics and elements of a ship has been carried out. The most frequently used methods of multicriteria optimization and their application to solving the problem of ship design characteristics substantiation, with taking into account the requirements to seakeeping and economic efficiency are considered. The multicriteria optimization results obtained by different methods are compared with the results of single-criteria optimization. Finally, numerical examples are implemented to demonstrate that an attempt to find a compromise solution often decrease the values of local criteria of optimality. It is established that the application of multi-criteria optimization methods for solving the ship design problems makes clear the role of each local optimality criteria and assess it influence on functional efficiency and design characteristics values.

多様性に注目した配電系統拡張のための多目的最適化手法の適用

This paper presents the application of multi-objective optimization methods for Network expansion planning. According to the electricity liberalization in fiscal year 2016, a suitable distribution method for both supply and demand selection is desired. Therefore, the distribution network expansion planning was studied in this research. In recent research, Controlled NSGA-Ⅱmethod regarding to the linkage distinction method using count box was being considered. This study proposes the same idea with an improvement to the method. It is also expected for an outcome which preserves the individual that supposed to be destroyed along the calculation process and also, necessary for wide solution.

The application of multi-objective optimization method for activated sludge process: a review.

The activated sludge process (ASP) is the most generally applied biological wastewater treatment approach. Depending on the design and specific application, activated sludge wastewater treatment plants (WWTPs) can achieve biological nitrogen (N) and phosphorus (P) removal, besides the removal of organic carbon substances. However, the effluent N and P limits are getting tighter because of increased emphasis on environmental protection, and the needs for energy conservation as well as the operational reliability. Therefore, the balance between treatment performance and cost becomes a critical issue for the operations of WWTPs, which necessitates a multi-objective optimization (MOO). Recent studies in this field have shown promise in utilizing MOO to address the multiple conflicting criteria (i.e. effluent quality, operation cost, operation stability), including studying the ASP models that are primarily responsible for the process, and developing the method of MOO in the wastewater treatment process, which facilitates better optimization of process performance. Based on a better understanding of the application of MOO for ASP, a comprehensive review is conducted to offer a clear vision of the advances, and potential areas for future research are also proposed in the field.

Network Expansion Planning using Improved Controlled NSGA-II

SUMMARY This paper presents the application of multiobjective optimization methods to network expansion planning. Distribution network expansion planning minimizes system cost and distribution loss while satisfying the constraints. Problem formulation yields combinatorial optimization problems that are difficult to solve due to their complexity. This research applies a genetic algorithm, which is a meta-heuristics method. The present study proposes a new method of multiobjective optimization: NSGA-II, SPEA2, and Controlled NSGA-II are assumed to be the best methods now. The proposed method introduces the concept of a linkage identification genetic algorithm, enabling more efficient searching than methods hitherto known. In the past, most research on network expansion planning did not include the load curve. This research demonstrates that the investigation must include the load curve. It also proposes a new method of search including the load curve.

A solution process for simulation-based multiobjective design optimization with an application in the paper industry

In this paper, we address some computational challenges arising in complex simulation-based design optimization problems. High computational cost, black-box formulation and stochasticity are some of the challenges related to optimization of design problems involving the simulation of complex mathematical models. Solving becomes even more challenging in case of multiple conflicting objectives that must be optimized simultaneously. In such cases, application of multiobjective optimization methods is necessary in order to gain an understanding of which design offers the best possible trade-off. We apply a three-stage solution process to meet the challenges mentioned above. As our case study, we consider the integrated design and control problem in paper mill design where the aim is to decrease the investment cost and enhance the quality of paper on the design level and, at the same time, guarantee the smooth performance of the production system on the operational level. In the first stage of the three-stage solution process, a set of solutions involving different trade-offs is generated with a method suited for computationally expensive multiobjective optimization problems using parallel computing. Then, based on the generated solutions an approximation method is applied to create a computationally inexpensive surrogate problem for the design problem and the surrogate problem is solved in the second stage with an interactive multiobjective optimization method. This stage involves a decision maker and her/his preferences to find the most preferred solution to the surrogate problem. In the third stage, the solution best corresponding that of stage two is found for the original problem.

Application of Multi-objective Optimization to Voltage and Reactive Power Control

This paper presents an application of multi-objective optimization methods for voltage and reactive power control (VQC) taking account of an operation margin. Multi-objective optimization has been developed based on genetic algorithms (Gas) with the characteristic of multi points search. An operation margin is considered to minimize generator reactive outputs and tap potions difference from the neutral. To make clear usability of the proposed method, results of applying the proposed method to a 15 bus system model and a 118 bus system model are compared to result of studies using the conventional weighting coefficients, and effectiveness of the proposed method is discussed.

Application of the Hybrid Multiobjective Optimization Methods on the Capacitive Voltage Divider

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper presents application of multiobjective optimization methods on a capacitive divider finite element model. Modeling is based on the differential evolution algorithm (DE), including the concept of the Pareto nondominance. Through calculations, this concept allows differential evolution algorithm variation in order to achieve uniformly distributed results on the Pareto front, including the lowest population size as possible. Selection step, as a part of the differential evolution method, is properly modified to improve the convergence of the algorithm. The entire research leads to a hybrid algorithm development. </para>