نتایج جستجو برای: cost tradeoff time value of money crashing nsga ii multi objective problem aoa network

تعداد نتایج: 21561243  

Fateme Ahmadi Boyaghchi, Mona Rahmatian

The present research proposes and optimizes the performance of a novel solar-driven combined cooling, heating, and power (CCHP) Kalina system for two seasons—winter and summer—based on exergy, exergo-economic, and exergo-environmental concepts applying a Non-dominated Sort Genetic Algorithm-II (NSGA-II) technique. Three criteria, i.e. daily exergy efficiency, total product cost rate, and to...

A redundancy allocation problem (RAP) is a well-known NP-hard problem that involves the selection of elements and redundancy levels to maximize the system reliability under various system-level constraints. In many practical design situations, reliability apportionment is complicated because of the presence of several conflicting objectives that cannot be combined into a single-objective functi...

Journal: :Inf. Sci. 2016
Wei Zheng Robert M. Hierons Miqing Li Xiaohui Liu Veronica Vinciotti

Regression testing is the process of retesting a system after it or its environment has changed. Many techniques aim to find the cheapest subset of the regression test suite that achieves full coverage. More recently, it has been observed that the tester might want to have a range of solutions providing different trade-offs between cost and one or more forms of coverage, this being a multi-obje...

. Hosseinzadeh-Lotfi E. Najafi N. Torabi R. Tavakkoli-Moghaddam,

This paper presented a new two-stage green supply chain network, in which includes two innovations. Firstly, it presents a new multi-objective model for a two-stage green supply chain problem that considers the amount o...

This study addresses the pickup and delivery problem for cross-docking strategy, in which shipments are allowed to be transferred from suppliers to retailers directly as well as through cross-docks. Usual models that investigate vehicle routing in cross-docking networks force all vehicles to stop at the cross-dock even if a shipment is about to a full truckload or the vehicle collects and deliv...

Hakimpour , Farshad, Maleki, Jamshid , Masoumi, Zohreh ,

Allocating urban land-uses to land-units with regard to different criteria and constraints is considered as a spatial multi-objective problem. Generating various urban land-use layouts with respect to defined objectives for urban land-use allocation can support urban planners in confirming appropriate layouts. Hence, in this research, a multi-objective optimization algorithm based on grid is pr...

2009
Darian Raad Alexander Sinske Jan van Vuuren

The design of a water distribution system (WDS) involves finding an acceptable trade-off between multiple conflicting objectives, particularly in terms of minimizing cost and maximizing system benefits (such as hydraulic reliability). The goal in multi-objective optimization is to find a set of design solutions which embodies an acceptable trade-off between these costs and benefits, enabling th...

The problem of maximizing the benefit from a specified number of a particular product with respect to the behavior of customer choices is regarded as revenue management. This managerial technique was first adopted by the airline industries before being widely used by many others such as hotel industries. The scope of this research is mainly focused on hotel revenue management, regarding which a...

2009
AMAR KISHOR SHIV PRASAD YADAV Amar Kishor Shiv Prasad Yadav

This paper considers the allocation of maximum reliability to a complex system, while minimizing the cost of the system, a type of multi-objective optimization problem (MOOP). Multi-objective Evolutionary Algorithms (MOEAs) have been shown in the last few years as powerful techniques to solve MOOP .This paper successfully applies a Nondominated sorting genetic algorithm (NSGA-II) technique to o...

2010
Elhadj Benkhelifa Michael Farnsworth Ashutosh Tiwari Meiling Zhu

The evolutionary approach in the design optimisation of MEMS is a novel and promising research area. The problem is of a multi-objective nature; hence, multi-objective evolutionary algorithms (MOEA) are used. The literature shows that two main classes of MOEA have been used in MEMS evolutionary design Optimisation, NSGA-II and MOGA-II. However, no one has provided a justification for using eith...

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