نتایج جستجو برای: non dominated sorting genetic algorithm
تعداد نتایج: 2547679 فیلتر نتایج به سال:
integrated production-distribution planning (pdp) is one of the most important approaches in supply chain networks. we consider a supply chain network (scn) to consist of multi suppliers, plants, distribution centers (dcs), and retailers. a bi-objective mixed integer linear programming model for integrating production-distribution designed here aim to simultaneously minimize total net costs in ...
Integrated production-distribution planning (PDP) is one of the most important approaches in supply chain networks. We consider a supply chain network (SCN) to consist of multi suppliers, plants, distribution centers (DCs), and retailers. A bi-objective mixed integer linear programming model for integrating production-distribution designed here aim to simultaneously minimize total net costs in ...
دراین رساله عملکرد موتورهای توربوفن از نظر ترمودینامیکی درشرایط خارج از نقطه طراحی بررسی می گردد. این بررسی شامل مقایسه نمودارهای عملکردی موتورهای توربوفن با نسبت کنارگذر بالا و پایین با یکدیگر نیز می باشد. در مدل ترمودینامیکی موتور توربوفن، از روش شبیه سازی مونت کارلو جهت بررسی تاثیر نامعینی های موجود در پارامترهای ورودی ثابت، از قبیل راندمان اتاق احتراق و ارزش حرارتی سوخت، بر روی عملکرد موتور...
Taking into account competitive markets, manufacturers attend more customer’s personalization. Accordingly, build-to-order systems have been given more attention in recent years. In these systems, the customer is a very important asset for us and has been paid less attention in the previous studies. This paper introduces a new build-to-order problem in the supply chain. This study focuses on bo...
NSGA methodology discussed in Section 3.1 suffers from three weaknesses: computational complexity, non-elitist approach and the need to specify a sharing parameter. An improved version of NSGA known as NSGA-II, which resolved the above problems and uses elitism to create a diverse Pareto-optimal front, has been subsequently presented (Deb et al 2002). The main features of NSGA-II are low comput...
We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN(2)) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-...
In this paper, a method based on Non-Dominated Sorting Genetic Algorithm (NSGA) has been presented for the Volt / Var control in power distribution systems with dispersed generation (DG). Genetic algorithm approach is used due to its broad applicability, ease of use and high accuracy. The proposed method is better suited for volt/var control problems. A multi-objective optimization problem has ...
This paper considers a scheduling problem of a set of independent jobs on unrelated parallel machines (UPMs) that minimizesthe maximum completion time (i.e., makespan or ), maximum earliness ( ), and maximum tardiness ( ) simultaneously. Jobs have non-identical due dates, sequence-dependent setup times and machine-dependentprocessing times. A multi-objective mixed-integer linear programmi...
....... The fast and elitist non-dominated sorting genetic algorithm (NSGA-II) contains a mechanism to sort individuals in a multi-objective optimization problem into non-dominated fronts, based on their performance in each optimization variable. When dealing with a bi-objective problem it is possible to carry-out the non-dominated sorting more efficiently, using the new sorting method presente...
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