Sharif Digital Repository

In this paper, we address a basic production planning problem with price dependent demand and stochastic yield of production. We use price and target quantity as decision variables to lower the risk of low yield. The value of risk control becomes more important especially for products with short life cycle. This is because, the profit implications of low yield might be unbearable in the short run. We apply Conditional Value at Risk (CVaR) to model the risk. CVaR measure is a coherent risk measure and thereby having nice conceptual and mathematical underpinnings. It is also widely used in practice. We consider the problem under general demand function and general distribution function 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... 

Macro-operators are sequences of actions that can guide a planner to achieve its goals faster by avoiding search for those sequences. However, using macro-operators will also increase the branching factor of choosing operators, and as a result making planning more complex and less efficient. On the other hand, the detection and exploitation of symmetric structures in planning problems can reduce the search space by directing the search process. In this paper, we present a new method for detecting symmetric objects through subgraph-isomorphism, and exploiting the extracted information in macrooperator selection. The method has been incorporated into HSP2, and tested on a collection of... 

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 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, we address a basic production planning problem with price dependent demand and stochastic yield of production. We use price and target quantity as decision variables to lower the risk of low yield. The value of risk control becomes more important especially for products with short life cycle. This is because, the profit implications of low yield might be unbearable in the short run. We apply Conditional Value at Risk (CVaR) to model the risk. CVaR measure is a coherent risk measure and thereby having nice conceptual and mathematical underpinnings. It is also widely used in practice. We consider the problem under general demand function and general distribution function of... 

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... 

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.... 

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... 

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... 

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... 

Reliability cost is considered as an inevitable criterion in expansion planning studies of distribution systems. However, nonlinear expressions of reliability indices aggravate complexity of planning studies. To address this issue, this letter proposes a novel method to linearize mathematical model of the reliability-based distribution expansion planning problem. Using this variant of reliability indices, reliability costs can easily be involved in mixed-integer linear programming model of distribution expansion planning. Validity of the derived expressions is tested by simulation results. © 1969-2012 IEEE  

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... 

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 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 study presents a motion planning algorithm to generate a feasible periodic solution for a hybrid system describing running by a three-dimensional (3-D), three-link, three-actuator, monopedal robot. In order to obtain a symmetric running gait along a straight line, the hybrid system consists of two stance phases and two flight phases. The motion planning algorithm is developed on the basis of a finite-dimensional optimisation problem with equality and inequality constraints. By extending the concept of hybrid zero dynamics to running, the authors propose a time-invariant control scheme that is employed at two levels to locally exponentially stabilise the generated periodic solution for... 

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....