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The paper presents the design of a three-layer printed reflectarray providing China coverage pattern for space applications. An optimization method was utilized in the design of the reflectarray to achieve a broad bandwidth of 11.85GHz-13.15GHz. To overcome the frequency band limitation of the reflectarray, the patch dimensions of the elements are optimized to match the required phase distributions...
This paper realized the establishment of grey model for the uncertain part in terms of the analysis of current loop model in permanent-magnet synchronous motor (PMSM) close-loop control system in order to acquire improvement of current tracking character. Based on this model and the combination of torque constant value Kt in online identified strategy, this algorithm could enhance the calculation...
This paper reports the characterization of bulk titanium deep etching using inductively coupled chlorine plasma using SU-8 as softmask. SU-8 has many advantages over the traditional employed hardmask, such as selective stripping, cost efficiency and the ability to accommodate ultra deep etching. The effects of process parameters (ICP source power, platen power and Cl2 flow rate) on etch rate, selectivity...
The logistic scheduling is a typical combinatorial optimization problem. Vehicle routing optimization is one of the most critical parts in logistics, and the Vehicle Routing Problem (VRP) is an important problem occurring in many distribution systems. This paper proposes an improved ant colony optimization algorithm to optimize the dynamic assignment to the Capacitated Vehicle Routing Problem (CVRP)...
In this paper, we first describe a multi-objective supply chain model and the optimization problem in Supply Chain Management (SCM), which includes measurements of cost, customer service fill rates and delivery flexibility. This model incorporates production and delivery. Then, we present an Ant Colony Optimization (ACO) application to the solution of some multi-objective optimization problems. We...
The purpose of this paper is to present a novel multi-agent cooperating learning method for the learning agents to share episodes beneficial to the exploitation of the accumulated knowledge and to utilize the learned reinforcement values efficiently. Further, taking the visited times into account, this paper proposes the multi-agent learning method that the learning agents share better policies beneficial...
Reinforcement learning (RL) is an efficient learning method for Markov decision processes (MDPs); ant colony system (ACS) is an efficient method for solving combinatorial optimization problems. Based on the update policy of reinforcement values in RL and the cooperating method of the indirect media communication in ACS, this paper proposes the Q-ACS multi-agent cooperating learning method for the...
Reinforcement learning (RL) is successfully applied to some dynamical and unpredictable domains. The Supply Chain Management (SCM) is NP-hard problem. Some proposed RL methods perform better than traditional tools for dynamic problem solving in SCM. It realizes on-line learning and performs efficiently in some applications, but RL agent reacts worse than some heuristic methods to sudden changes in...
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