Sharif Digital Repository

Integrated transmission expansion planning (TEP) and generation expansion planning (GEP) with Wind Farms (WFs) is addressed in this paper. The optimal number of expanded lines, the optimal capacity of WFs installed capacity, and the optimal capacity of wind farms lines (WFLs) are determined through a new TEP optimization model. Furthermore, the optimum capacity additions including conventional generating units is obtained in the proposed model. The Benders decomposition approach is used for solving the optimization problem, including a master problem and two sub-problems with internal scenario analysis. In order to reduce the computational burden of the multi-year and multi-objective... 

In this paper, the path planning problem of special hyper-redundant manipulator with lockable joints is solved using particle swarm optimization. There is a locking mechanism in each link of this tendon-actuated manipulator. At any time, all links of the manipulator must be locked except one. Then by pulling the cables, the configuration of the corresponding link will change and the manipulator will tilt to its new position. Therefore, by unlocking the links in sequence and pulling the cables, any desirable configuration of manipulator can be reached. In path planning problem, the desired path of the end-effector is given and the optimum sequence of switching (discrete) and the optimum... 

In this paper, the path planning problem of special hyper-redundant manipulator with lockable joints is solved using particle swarm optimization. There is a locking mechanism in each link of this tendon-actuated manipulator. At any time, all links of the manipulator must be locked except one. Then by pulling the cables, the configuration of the corresponding link will change and the manipulator will tilt to its new position. Therefore, by unlocking the links in sequence and pulling the cables, any desirable configuration of manipulator can be reached. In path planning problem, the desired path of the end-effector is given and the optimum sequence of switching (discrete) and the optimum... 

In deregulated power systems, distribution network operators (DNO) are responsible for maintaining the proper operation and efficiency of distribution networks. This is achieved traditionally through specific investments in network components. The event of distributed generation (DG) has introduced new challenges to these distribution networks. The role of DG units must be correctly assessed to optimise the overall operating and investment cost for the whole system. However, the distributed generation owners (DGOs) have different objective functions which might be contrary to the objectives of DNO. This study presents a long-term dynamic multi-objective model for planning of distribution... 

This paper presents a long-term dynamic multi-objective planning model for distribution network expansion along with distributed energy options. The proposed model optimizes two objectives, namely costs and emissions and determines the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on distributed generation units and network reinforcements over the planning period. An efficient two-stage heuristic method is proposed to solve the formulated planning problem. The effectiveness of the proposed model is demonstrated by applying it to a distribution network and comparing the simulation results with other methods and models  

Today's world energy-related challenges, ranging from anthropogenic climate change to continuous growth of demand for different energy forms, have enforced planners of energy systems (ESs) to concentrate on more optimal and eco-friendly operation and/or expansion planning methodologies. In this context, increased interdependencies of gas, heat and electricity ESs have recently encouraged the planners to design operation and/or expiation strategies in an integrated manner in favor of a new concept, the so-called “Energy Hub” (EH). Although this concept has been employed so far in a multitude of studies, but its real nature, advantages, difficulties, importance or inevitability aspect, and... 

Cat free fall righting maneuverer has inspired many aerial, space and legged robotic research. Conservation of angular momentum principle is used to derive the inverse differential kinematic and TMT vector form dynamics of the motion for three robotic models: a two-link model, a three-link model with tail, and a comprehensive eight-link model with the addition of legs. The path planning problem in the presence of geometric and kinematic constraints is addressed using a novel singularity free single shooting optimization method. While a 2 DOF torso is sufficient to perform a full maneuver, the addition of the tail reduces the time and increases the maneuverability despite the leg motions that... 

Since that heuristic state space planners have been very successful in classical planning, this approach is currently the most popular strategy in dealing with temporal planning, too. However, all current state-space temporal planners use a search method known as decision epoch planning, which is not complete for problems with required concurrency. In theory, this flaw can be overcome by employing another search method, called temporally lifted progression planning. In this paper, we show that there are two major problems which, if not tackled properly, can cause the latter method to be very inefficient in practice. The first problem is dealing with the remarkably large state space of... 

Decentralized supply chain management is found to be significantly relevant in today’s competitive markets. Production and distribution planning is posed as an important optimization problem in supply chain networks. Here, we propose a multi-period decentralized supply chain network model with uncertainty. The imprecision related to uncertain parameters like demand and price of the final product is appropriated with stochastic and fuzzy numbers. We provide mathematical formulation of the problem as a bi-level mixed integer linear programming model. Due to problem’s convolution, a structure to solve is developed that incorporates a novel heuristic algorithm based on Kth-best algorithm, fuzzy... 

Decentralized supply chain management is found to be significantly relevant in today’s competitive markets. Production and distribution planning is posed as an important optimization problem in supply chain networks. Here, we propose a multi-period decentralized supply chain network model with uncertainty. The imprecision related to uncertain parameters like demand and price of the final product is appropriated with stochastic and fuzzy numbers. We provide mathematical formulation of the problem as a bi-level mixed integer linear programming model. Due to problem’s convolution, a structure to solve is developed that incorporates a novel heuristic algorithm based on Kth-best algorithm, fuzzy... 

A hyper-redundant manipulator is made by mounting the serial and/or parallel mechanisms on top of each other as modules. In discrete actuation, the actuation amounts are a limited number of certain values. It is not feasible to solve the kinematic analysis problems of discretely actuated hyper-redundant manipulators (DAHMs) by using the common methods, which are used for continuous actuated manipulators. In this paper, a new method is proposed to solve the trajectory tracking problem in a static prescribed obstacle field. To date, this problem has not been considered in the literature. The removing first collision (RFC) method, which is originally proposed for solving the inverse kinematic... 

A hyper-redundant manipulator is made by mounting the serial and/or parallel mechanisms on top of each other as modules. In discrete actuation, the actuation amounts are a limited number of certain values. It is not feasible to solve the kinematic analysis problems of discretely actuated hyper-redundant manipulators (DAHMs) by using the common methods, which are used for continuous actuated manipulators. In this paper, a new method is proposed to solve the trajectory tracking problem in a static prescribed obstacle field. To date, this problem has not been considered in the literature. The removing first collision (RFC) method, which is originally proposed for solving the inverse kinematic... 

In this paper, a generalized intelligent water drops algorithm (IWD) for solving robot path planning problem is proposed. The authors want to reduce the time of reaching the optimal solution as much as possible. To do this, some new heuristic operators and a multi section graph model of environment is introduced. The authors divide graph to equal sections and compare behaviour of the solutions (paths) in each section with behaviour of them in other sections. This comparison uses a fuzzy inference system. Base on this comparison, a fuzzy number is assigned to each part of solutions. This fuzzy number determines the worth of a solution in a section. Less worth solutions need more improvement.... 

Robot navigation is a challenging problem in robotics, which involves determining of robot positioning relative to objects in the environment, and also the mobility of robot through obstacles without colliding into them. The former is known as localization, while the latter is called motion planning. This paper introduces a roadmap method for solving motion planning problem in a dynamic environment based on Generalized Voronoi Diagram (GVD). The efficiency of the proceeding work is verified by examining it in a sample home environment. © 2008 Springer-Verlag  

In rail transportation, the process of finding the optimal movement of freight goods is considered a tactical level of rail planning. Solving this problem requires one simultaneously to address the railroad blocking problem and the train dispatching problem, which is difficult. Additionally, when these problems are represented by mathematical relations, application of the solution leads to unexpected results in the real world. The main objective of this research was to build a simulation environment to represent the key behaviours of typical and applicable constraints of a railway system. This environment provides a tool with which to evaluate different decisions among a list of candidate... 

The learning effects of the workers and machine deterioration in an aggregate production planning (APP) problem have not been taken into account in the literature yet. These factors affect the performance of any real-world production system and require attention. In this paper, a bi-objective optimization model is developed for an APP problem with labor learning effect and machine deterioration. The first objective of this model maximizes the profit by improving learning and reducing the failure cost of the system. The second objective function minimizes the costs associated with repairs and deterioration, which depend on the failure rate of the machines in the production periods. The aim of... 

Motion planning is a key factor in enhancing the autonomy level of unmanned flying vehicles. A new dynamic hybrid algorithm is developed to solve the motion planning problem in real-time using a heuristic optimization approach. The proposed algorithm effectively combines desired features such as rapid convergence to an optimal path with reduced computational effort. In addition to the terrain obstacles, the proposed algorithm is able to avoid random threats that may arise sporadically in the terrain. Using the maneuver automaton concept, nonlinear dynamic model and performance constraints are also considered in the process of motion planning to further ensure feasible trajectories.... 

Motion planning and trajectory control are two basic challenges of unmanned vehicles. In motion planning problem, feasible trajectories are developed while nonlinear dynamic model and performance constraints of the vehicle under utility are considered. In this study, motion planning is performed via an enhanced particle swarm optimization algorithm. The resulting offline generated trajectories are tracked using a nonlinear trajectory control system methodology. The Lyapunov-based constrained backstepping approach and command filters are utilized in designing the trajectory control system. Command filters smoothen the input signals and provide their derivatives. Evaluation of the proposed... 

In this paper, a multi-agent framework is proposed to address the expansion planning problem in a restructured active distribution network. In this framework, the objective and techno-economic constraints of participating agents are addressed in the expansion planning of power network and DER assets as well as the network and DERs optimal operation management. The agents include distributed generator owners and load aggregators which participate along with the distribution network operator (DNO) in the active distribution network planning. The proposed framework is formulated as a bi-level optimization problem with multi-lower levels in which the DNO optimizes the network expansion planning...