Abstract: The objective of the Economic Dispatch(ED) Problems
of electric power generation is to schedule the committed generating
units outputs so as to meet the required load demand at minimum
operating cost while satisfying all units and system equality and
inequality constraints. This paper presents a new method of ED
problems utilizing the Max-Min Ant System Optimization.
Historically, traditional optimizations techniques have been used,
such as linear and non-linear programming, but within the past
decade the focus has shifted on the utilization of Evolutionary
Algorithms, as an example Genetic Algorithms, Simulated Annealing
and recently Ant Colony Optimization (ACO). In this paper we
introduce the Max-Min Ant System based version of the Ant System.
This algorithm encourages local searching around the best solution
found in each iteration. To show its efficiency and effectiveness, the
proposed Max-Min Ant System is applied to sample ED problems
composed of 4 generators. Comparison to conventional genetic
algorithms is presented.
Abstract: Over Current Relays (OCRs) and Directional Over Current Relays (DOCRs) are widely used for the radial protection and ring sub transmission protection systems and for distribution systems. All previous work formulates the DOCR coordination problem either as a Non-Linear Programming (NLP) for TDS and Ip or as a Linear Programming (LP) for TDS using recently a social behavior (Particle Swarm Optimization techniques) introduced to the work. In this paper, a Modified Particle Swarm Optimization (MPSO) technique is discussed for the optimal settings of DOCRs in power systems as a Non-Linear Programming problem for finding Ip values of the relays and for finding the TDS setting as a linear programming problem. The calculation of the Time Dial Setting (TDS) and the pickup current (Ip) setting of the relays is the core of the coordination study. PSO technique is considered as realistic and powerful solution schemes to obtain the global or quasi global optimum in optimization problem.
Abstract: This paper deals with the project selection problem. Project selection problem is one of the problems arose firstly in the field of operations research following some production concepts from primary product mix problem. Afterward, introduction of managerial considerations into the project selection problem have emerged qualitative factors and criteria to be regarded as well as quantitative ones. To overcome both kinds of criteria, an analytic network process is developed in this paper enhanced with fuzzy sets theory to tackle the vagueness of experts- comments to evaluate the alternatives. Additionally, a modified version of Least-Square method through a non-linear programming model is augmented to the developed group decision making structure in order to elicit the final weights from comparison matrices. Finally, a case study is considered by which developed structure in this paper is validated. Moreover, a sensitivity analysis is performed to validate the response of the model with respect to the condition alteration.
Abstract: Among many different methods that are used for
optimizing different engineering problems mathematical (numerical)
optimization techniques are very important because they can easily
be used and are consistent with most of engineering problems. Many
studies and researches are done on stability analysis of three
dimensional (3D) slopes and the relating probable slip surfaces and
determination of factors of safety, but in most of them force
equilibrium equations, as in simplified 2D methods, are considered
only in two directions. In other words for decreasing mathematical
calculations and also for simplifying purposes the force equilibrium
equation in 3rd direction is omitted. This point is considered in just a
few numbers of previous studies and most of them have only given a
factor of safety and they haven-t made enough effort to find the most
probable slip surface. In this study shapes of the slip surfaces are
modeled, and safety factors are calculated considering the force
equilibrium equations in all three directions, and also the moment
equilibrium equation is satisfied in the slip direction, and using
nonlinear programming techniques the shape of the most probable
slip surface is determined. The model which is used in this study is a
3D model that is composed of three upper surfaces which can cover
all defined and probable slip surfaces. In this research the meshing
process is done in a way that all elements are prismatic with
quadrilateral cross sections, and the safety factor is defined on this
quadrilateral surface in the base of the element which is a part of the
whole slip surface. The method that is used in this study to find the
most probable slip surface is the non-linear programming method in
which the objective function that must get optimized is the factor of
safety that is a function of the soil properties and the coordinates of
the nodes on the probable slip surface. The main reason for using
non-linear programming method in this research is its quick
convergence to the desired responses. The final results show a good
compatibility with the previously used classical and 2D methods and
also show a reasonable convergence speed.
Abstract: In this paper, a method for deriving a group priority vector in the Fuzzy Analytic Network Process (FANP) is proposed. By introducing importance weights of multiple decision makers (DMs) based on their experiences, the Fuzzy Preferences Programming Method (FPP) is extended to a fuzzy group prioritization problem in the FANP. Additionally, fuzzy pair-wise comparison judgments are presented rather than exact numerical assessments in order to model the uncertainty and imprecision in the DMs- judgments and then transform the fuzzy group prioritization problem into a fuzzy non-linear programming optimization problem which maximize the group satisfaction. Unlike the known fuzzy prioritization techniques, the new method proposed in this paper can easily derive crisp weights from incomplete and inconsistency fuzzy set of comparison judgments and does not require additional aggregation producers. Detailed numerical examples are used to illustrate the implement of our approach and compare with the latest fuzzy prioritization method.
Abstract: In today-s global and competitive market,
manufacturing companies are working hard towards improving their
production system performance. Most companies develop production
systems that can help in cost reduction. Manufacturing systems
consist of different elements including production methods,
machines, processes, control and information systems. Human issues
are an important part of manufacturing systems, yet most companies
do not pay sufficient attention to them. In this paper, a workforce
planning (WP) model is presented. A non-linear programming model
is developed in order to minimize the hiring, firing, training and
overtime costs. The purpose is to determine the number of workers
for each worker type, the number of workers trained, and the number
of overtime hours. Moreover, a decision support system (DSS) based
on the proposed model is introduced using the Excel-Lingo software
interfacing feature. This model will help to improve the interaction
between the workers, managers and the technical systems in
manufacturing.