Search results for "Multi-Objective Optimization."
showing 10 items of 189 documents
APROS-NIMBUS: Dynamic Process Simulator and Interactive Multiobjective Optimization in Plant Automation
2013
Abstract Virtual commissioning of chemical plants often involves a dynamic simulator and an optimization method. This paper demonstrates the integration of APROS, a dynamic process simulator and IND-NIMBUS, an interactive multiobjective optimization software. We implement a multiobjective concentration control problem in APROS involving conflicting objectives and employ a decision maker to interact with IND-NIMBUS and express his preference information to finally obtain his most preferred solution. The results of this study show that APROS and IND-NIMBUS can be integrated and an interactive multiobjective optimization method can help the decision maker in exploring trade-offs among conflict…
Interactive Multiobjective Optimization in Lot Sizing with Safety Stock and Safety Lead Time
2021
In this paper, we integrate a lot sizing problem with the problem of determining optimal values of safety stock and safety lead time. We propose a probability of product availability formula to assess the quality of safety lead time and a multiobjective optimization model as an integrated lot sizing problem. In the proposed model, we optimize six objectives simultaneously: minimizing purchasing cost, ordering cost, holding cost and, at the same time, maximizing cycle service level, probability of product availability and inventory turnover. To present the applicability of the proposed model, we consider a real case study with data from a manufacturing company and apply the interactive NAUTI…
Supporting the Sustainable Energy Transition in the Canary Islands: Simulation and Optimization of Multiple Energy System Layouts and Economic Scenar…
2021
The Canary Islands have great potential for the implementation of sustainable energy systems due to its availability of natural resources. The archipelago is not connected to the mainland electricity grid and the current generation system is mainly based on traditional fossil fuel. Therefore, the islands strongly dependent on fuel importations, with high costs due to logistics. Furthermore, due to the inadequate coverage of residential heating and cooling needs, the per capita energy consumption is far below the Spanish national average. This occurrence has inspired an intense debate on the current development model of the Canary Archipelago, which has led to the implementation of actions a…
Efficient evolutionary approach to approximate the Pareto-optimal set in multiobjective optimization, UPS-EMOA
2010
Solving real-life engineering problems requires often multiobjective, global, and efficient (in terms of objective function evaluations) treatment. In this study, we consider problems of this type by discussing some drawbacks of the current methods and then introduce a new population-based multiobjective optimization algorithm UPS-EMOA which produces a dense (not limited to the population size) approximation of the Pareto-optimal set in a computationally effective manner.
Constrained Robust MultiObjective Optimization for Reactive Design in Distribution Systems
2006
This paper presents a new formulation including robustness of solution of constrained multiobjective design or reactive power compensation. The algorithm used for optimization is the NSGA-II (Non dominated Sorting Genetic Algorithm II) with a special crowded comparison operator for constraints handling. The need for including the issue of robustness of solutions derives from the simple observation that loads are uncertain in distribution systems and their estimation is often affected by errors. In design problems it is desirable to consider the loads with a certain range of variation. In this paper the NSGA-II algorithm is applied to efficiently solve the issue and the solutions attained co…
A New Meta-Heuristic Multi-Objective Approach For Optimal Dispatch of Dispersed and Renewable Generating Units in Power Distribution Systems
2011
The application of stochastic methods in engineering research and optimization has been increasing over the past few decades. Ant Colony Optimization, in particular, has been attracting growing attention as a promising approach both in discrete and continuous domains. The present work proposes a multi-objective Ant Colony Optimization for continuous domains showing good convergence properties and uniform coverage of the non-dominated front. These properties have been proved both with mathematical test functions and with a complex real world problem. Besides the second part of the chapter presents the application of the new algorithm to the problem of optimal dispatch of dispersed power gene…
Multi-objective Optimization of Energy Hubs at the Crossroad of Three Energy Distribution Networks
2016
This paper provides a multi-objective optimization framework aimed at the management of a multi-carrier energy system involving both electricity and hydrogen. Using the concept of the multi-carrier hub, the proposed system has been modelled in order to define completely every energy flow inside the plant. After that, a heuristic multi-objective optimization algorithm, the Non-dominated Sorting Genetic Algorithm II, has been implemented for the energy management of the plant, taking into account simultaneously three different objective functions related to economic and technical goals. This optimization process provides the set point defining the working configuration of the plant for a dayl…
QoS-Aware Fault Detection in Wireless Sensor Networks
2013
Wireless sensor networks (WSNs) are a fundamental building block of many pervasive applications. Nevertheless the use of such technology raises new challenges regarding the development of reliable and fault-tolerant systems. One of the most critical issues is the detection of corrupted readings amidst the huge amount of gathered sensory data. Indeed, such readings could significantly affect the quality of service (QoS) of the WSN, and thus it is highly desirable to automatically discard them. This issue is usually addressed through “fault detection” algorithms that classify readings by exploiting temporal and spatial correlations. Generally, these algorithms do not take into account QoS re…
Finding near-perfect parameters for hardware and code optimizations with automatic multi-objective design space explorations
2012
Summary In the design process of computer systems or processor architectures, typically many different parameters are exposed to configure, tune, and optimize every component of a system. For evaluations and before production, it is desirable to know the best setting for all parameters. Processing speed is no longer the only objective that needs to be optimized; power consumption, area, and so on have become very important. Thus, the best configurations have to be found in respect to multiple objectives. In this article, we use a multi-objective design space exploration tool called Framework for Automatic Design Space Exploration (FADSE) to automatically find near-optimal configurations in …
Automatic multi-objective optimization of parameters for hardware and code optimizations
2011
Recent computer architectures can be configured in lots of different ways. To explore this huge design space, system simulators are typically used. As performance is no longer the only decisive factor but also e.g. power usage or the resource usage of the system it became very hard for designers to select optimal configurations. In this article we use a multi-objective design space exploration tool called FADSE to explore the vast design space of the Grid Alu Processor (GAP) and its post-link optimizer called GAPtimize. We improved FADSE with techniques to make it more robust against failures and to speed up evaluations through parallel processing. For the GAP, we present an approximation o…