effective design of sustainable buildings results from an accurate optimization process of all the variables that are involved and interrelated in meeting the various sustainability goals in the field of energy, indoor environmental quality, water management, and sustainable materials [1][2]. For that reason, current frameworks for the building design process rely on a high degree of interdisciplinary collaboration between all the professionals involved (architects, engineers, consultants, etc.) from the early design stage to the delivery of the building. Such frameworks are often referred to as “integrated design process” (IDP), for example in IEA Task 23 [3], “integrated delivery…
Start, even as simply as writing an essay, but a good one, it requires a start and it requires the writer to start with his or her magic pen to let the article flow. Operation research is my new start. In the field of operation research, optimization attracts me with its unique beauty. Nonlinear optimization, linear optimization, integer optimization, decision diagram all these fields of study start letting me know what I’m good at and what I will devote my life in. Starting a PhD in operation…
the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and self-organization \cite{dorigo2007}. The name was firstly coined by Beni and Weng in the 1989 in order to present cellular robotic systems as capable of being intelligent \cite{beni1989}. Cellular Robotic Systems are collections of autonomous, non-synhronized, non-intelligent robots cooperating to achieve some given tasks \cite{beni1993}. In area of…
2.3.2 PARTICLE SWARM OPTIMIZATION (PSO) Particle Swarm Optimization [27] is a population-based stochastic optimization developed by Dr. Ebehart and Dr. Kennedy in 1995, inspired by social behavior of bird flocking or fish schooling. In PSO, each single solution is a “bird” (particle) in the search space of food (the best solution). All particles have fitness values evaluated by the fitness function (the cost function for ELD problem), and have velocities that direct the “flying” (or evaluation)…
important factors; Familiarity, Simplification, and Clarity, are to be considered when developing such models. The greater the modeler’s familiarity with the relationships between competing activities and the limitations of the resources, the greater the likelihood of generating a usable model. Treating the problem from as many perspectives as possible such as various levels, horizontal and vertical helps in this regard. Linear models are always simplifications…
In this section, we provide details of the four modules of this invention. However, any one module of this invention can’t solve our problem alone. It is the interaction of all parts that allow the user to understand and improve the optimization models. We begin by defining the optimization problem. Our objective is to maximize or minimize the sum of objective terms by selecting optimal feasible levels of the independent variables. The set of process limits or constraints define the feasible…
Traveling Salesman Problem (TSP) is one of combinatorial optimization problems. X TSP is NP-hard problem which defined as a set of cities and each city should be visited once with minimum tour length. This paper solved this problem using Firefly Algorithm (FA) and k-means clustering by three steps: cluster the nodes, finding optimal path in each cluster and connect the clusters. The first step is to divide all nodes into sub-problems using k-means clustering, the second step is to use FA to find…
2.RELATED WORK The artificial bee colony (ABC), an optimization technique is based upon the intelligent moving behavior of honey bee swarm was proposed by Karaboga in 2005. This kind of new Meta heuristic is inspired by the clever foraging behavior of honey bee swarm. The criteria presented in the work is for numerical function optimization. The advantage of ABC is that the global search ability in the algorithm is implemented by introducing neighborhood source production mechanism. Rao et al.…
METHODOLOGY To optimize the losses of given system which will simultaneously upgrade the voltage at every bus, following methodology is opted which also includes the calculation of required shunt compensation. There are two cases: Case 1: Base case The problem formed is a non linear constrained optimization problem. Interior point method is used to solve this problem. The interior-point approach to constrained minimization is to solve a sequence of approximate minimization problems. It reaches…
Linear programming which is also known as “Linear Optimization” is a way to achieve best outcomes in a Mathematical Model using different linear solutions .Linear Programming is a special case of Mathematical Optimization .Linear programming can be applied to a wide variety of fields of study, and has proved useful in planning, routing, scheduling, assignment, and design, such as in transportation or manufacturing industries. The method of Linear Programming was originally developed by American…