The City-Climber robot is a novel wall-climbing robot developed at The City College of New York that has the capability to move on floors, climb walls, walk on ceilings and transit between them. In this paper, we firs...
详细信息
The City-Climber robot is a novel wall-climbing robot developed at The City College of New York that has the capability to move on floors, climb walls, walk on ceilings and transit between them. In this paper, we first develop the dynamic model of the City-Climber robot when it travel on different surfaces, i.e., floors, walls and ceilings, respectively. Then, we present a path planning method for the City-Climber robot using mixed integer linear programming (MILP) in three-dimensional (3-D) building environments that consist of objects with primitive geometrical shapes. MILP provides an optimization framework that can directly incorporate dynamic constraints with logical constraints such as obstacle avoidance and waypoint selection. In order to use MILP to solve the obstacle avoidance problem, we simplify and decouple the robot dynamic model into a linear system by introducing a restricting admissible controller. The decoupled model and obstacle can be rewritten as a linear program with mixed-integerlinear constraints that account for the collision avoidance. A key benefit of this approach is that the path optimization can be readily solved using the AMPL and CPLEX optimization software with a MATLAB interface. Simulation results show that the framework of MILP is well suited for path planning and obstacle avoidance problems for the wall-climbing robot in 3-D environments. (C) Koninklijke Brill NV, Leiden and The Robotics Society of Japan, 2010
In this paper, a multi-objective mixed-integerlinearprogramming model is developed to design a hybrid PV-hydrogen renewable energy system considering two objective func-tions;minimizing total life costs and loss pro...
详细信息
In this paper, a multi-objective mixed-integerlinearprogramming model is developed to design a hybrid PV-hydrogen renewable energy system considering two objective func-tions;minimizing total life costs and loss probability of power supply. The decisions of the hybrid system include the number of PV panels, the number of hydrogen tanks, the number of electrolyzers, the number of fuel cells, and quantity of hydrogen stored over time. An exact method embedded in GAMS software is used to solve the developed model. The model is validated using an electrical testing lab in Saudi Arabia with hourly power demand. Different plans are chosen from the obtained optimal Pareto solutions. For example, one of the plans found that a hybrid system with 212 PV panels, 617 hydrogen tanks, 30 electrolyzers, and 21 fuel cells is sufficient to satisfy the electrical testing lab load with an annual cost of $61663, the loss of power supply probability is 10%, and the CO2 saving of 214,882 kg of CO2. The results indicated the feasibility of combining an electro-lyzer, hydrogen tank storage, and fuel cell with a renewable energy system;however, the cost of energy generated is still high because of the high investment cost. Furthermore, the findings revealed that hydrogen technologies are appealing as an energy storage solution for intermittent renewable energy systems and in other applications such as trans-portation, residential, and industrial sectors. In addition, the findings demonstrated the possibility of using renewable energy as a source of energy, namely, in Saudi Arabia. However, weather conditions, geomorphological conditions, and climatic dependence on hydrogen fuel cell technology can harm the energy yields produced by renewable energy systems.(c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Trains running through railway lines often accumulate some delay. When this happens, rescheduling and rerouting decisions must be quickly taken in real time. Despite the fact that even a single wrong decision may dete...
详细信息
Trains running through railway lines often accumulate some delay. When this happens, rescheduling and rerouting decisions must be quickly taken in real time. Despite the fact that even a single wrong decision may deteriorate the performance of the whole railway network, this complex optimization task is still basically performed by human operators. In very recent years, the interest of train operators to implement automated decision systems has grown. Not incidentally, the railway application section (RAS) of INFORMS has issued a challenge devoted to this problem concomitantly with the INFORMS Annual Meeting 2012. In this article, we describe two heuristic approaches to solve the RAS problem based on a mixed integer linear programming formulation, and we report computational results on the three RAS instances and on an additional set of instances defined on a more congested network. Computational results on the challenge test bed show that our algorithms positively compare with other approaches to the RAS problem. (c) 2013 Wiley Periodicals, Inc. NETWORKS, Vol. 62(4), 315-326 2013
This work presents a method of finding near global optima to minimum-time trajectory generation problems for systems that would be linear if it were not for the presence of Coulomb friction. The required final state o...
详细信息
This work presents a method of finding near global optima to minimum-time trajectory generation problems for systems that would be linear if it were not for the presence of Coulomb friction. The required final state of the system is assumed to be maintainable by the system, and the input bounds are assumed to be large enough so that the role of maintaining zero acceleration during finite time intervals of zero velocity (the role of static friction) can always be assumed by the input. Other than the previous work for generating minimum-time trajectories for robotic manipulators for which the path in joint space is already specified, this work represents, to the best of our knowledge, the first approach for generating near global optima for minimum-time problems involving a non-linear class of dynamic systems. The reason the optima generated are near global optima instead of exactly global optima is due to a discrete-time approximation of the system (which is usually used anyway to simulate such a system numerically). The method closely resembles previous methods for generating minimum-time trajectories for linear systems, where the core operation is the solution of a Phase I linearprogramming problem. For the non-linear systems considered herein. the core operation is instead the solution of a mixed integer linear programming problem. Copyright (C) 2001 John Wiley & Sons, Ltd.
This paper deals with Maximally Balanced Connected Partition (MBCP) problem. It introduces a mixed integer linear programming (MILP) formulation of the problem with polynomial number of variables and constraints. Also...
详细信息
This paper deals with Maximally Balanced Connected Partition (MBCP) problem. It introduces a mixed integer linear programming (MILP) formulation of the problem with polynomial number of variables and constraints. Also, a variable neighborhood search (VNS) technique for solving this problem is presented. The VNS implements the suitable neighborhoods based on changing the component for an increasing number of vertices. An efficient implementation of the local search procedure yields a relatively short running time. The numerical experiments are made on instances known in the literature. Based on the MILP model, tests are run using two MILP solvers, CPLEX and Gurobi. It is shown that both solvers succeed in finding optimal solutions for all smaller and most of medium scale instances. Proposed VNS reaches most of the optimal solutions. The algorithm is also successfully tested on large scale problem instances for which optimal solutions are not known. (C) 2014 Elsevier Inc. All rights reserved.
Consideration was given to the a priori formulation of the multistage problem of stochastic programming with a quantile criterion which is reducible to the two-stage problem. Equivalence of the two-stage problems with...
详细信息
Consideration was given to the a priori formulation of the multistage problem of stochastic programming with a quantile criterion which is reducible to the two-stage problem. Equivalence of the two-stage problems with the quantile criterion in the a priori and a posteriori formulations was proved for the general case. The a posteriori formulation of the two-stage problem was in turn reduced to the equivalent problem of mixed integer linear programming. An example was considered.
This paper deals with the global solution of the general multi-parametric mixed integer linear programming problem with uncertainty in the entries of the constraint matrix, the right-hand side vector, and in the coeff...
详细信息
This paper deals with the global solution of the general multi-parametric mixed integer linear programming problem with uncertainty in the entries of the constraint matrix, the right-hand side vector, and in the coefficients of the objective function. To derive the piecewise affine globally optimal solution, the steps of a multi-parametric branch-and-bound procedure are outlined, where McCormick-type relaxations of bilinear terms are employed to construct suitable multi-parametric under- and overestimating problems. The alternative of embedding novel piecewise affine relaxations of bilinear terms in the proposed algorithmic procedure is also discussed.
Owing to the revolution in sustainable and green manufacturing the production planning and network design of closed loop supply chain concept has got the attention of researchers and managers. In this paper, a multi-p...
详细信息
Owing to the revolution in sustainable and green manufacturing the production planning and network design of closed loop supply chain concept has got the attention of researchers and managers. In this paper, a multi-product, multi-facility capacitated closed-loop supply chain framework is proposed in an uncertain environment including reuse, refurbish, recycle and disposal of parts. The uncertainty related to demand, fraction of parts recovered for different product recovery processes, product acquisition cost, purchasing cost, transportation cost, processing, and set-up cost is handled with fuzzy numbers. A fuzzy mixed integer linear programming model is proposed to decide optimally the location and allocation of parts at each facility and number of parts to be purchased from external suppliers in order to maximise the profit of organisation. The proposed solution methodology is able to generate a balanced solution between the feasibility degree and degree of satisfaction of the decision maker. The proposed model has been tested with an illustrative example.
This paper makes use of recent advances in mixed integer linear programming (MILP) to conduct a preliminary design study on the combinatorial optimal placement of thyristor controlled phase shifter transformers (TCPST...
详细信息
This paper makes use of recent advances in mixed integer linear programming (MILP) to conduct a preliminary design study on the combinatorial optimal placement of thyristor controlled phase shifter transformers (TCPSTs) in large-scale power systems. The procedure finds the number, network location, and settings of phase shifters that maximize system loadability under the dc load flow model, subject to limits on the installation investment or total number of TCPSTs. It also accounts for active flow and generation limits, and phase shifter constraints. Simulation results are presented for the IEEE 24-, 118-, and 300-bus systems, as well as a 904-bus network. The principal characteristics of our approach are compared with those of other published flexible ac system transmission (FACTS) allocation methods.
Cloudlet provides services with low latency and high bandwidth. Some research addresses the resource allocation problem in the cloudlet-based mobile cloud computing environment. However, there are few works considerin...
详细信息
Cloudlet provides services with low latency and high bandwidth. Some research addresses the resource allocation problem in the cloudlet-based mobile cloud computing environment. However, there are few works considering how to optimize resource allocation while satisfying users' requirements in multicloudlet situations. To solve this problem, a two-stage optimization strategy is proposed. First, a cloudlet selection model based on mixed integer linear programming (MILP) is proposed to obtain the cloudlet for mobile users by optimizing latency and mean reward. Second, a resource allocation model based on MILP is presented to allocate resources in the selected cloudlet by optimizing reward and mean resource usage. A comparison of resource allocation is analyzed with a cloudlet selection model based on MILP and an existing cloudlet selection strategy in the multi-cloudlet environment. From the simulation, our proposed strategy has better performance in terms of the access latency, the system reward and the resource usage.
暂无评论