A heuristic method for the vehicle routing problem with mixed deliveries and pickups

The vehicle routing problem with deliveries and pickups is a challenging extension to the vehicle routing problem that lately attracted growing attention in the literature. This paper investigates the relationship between two versions of this problem, called “mixed” and “simultaneous”. In particular, we wish to know whether a solution algorithm designed for the simultaneous case can solve the mixed case. To this end, we implement a metaheuristic based on reactive tabu search. The results suggest that this approach can yield good results.     

The memetic self-organizing map approach to the vehicle routing problem

The paper presents an extension of the self- organizing map (SOM) by embedding it into an evolutionary algorithm to solve the Vehicle Routing Problem (VRP). We call it the memetic SOM. The approach is based on the standard SOM algorithm used as a main operator in a population based search. This operator is combined with other derived operators specifically dedicated for greedy insertion moves, a fitness evaluation and a selection operator. The main operators have a similar structure based on the closest point findings and local moves performed in the plane. They can be interpreted as performing parallels and massive insertions, simulating the behavior of agents which interact continuously, having localized and limited abilities. This self-organizing process is intended to allow adaptation to noisy data as well as to confer robustness according to demand fluctuation. Selection is intended to guide the population based search toward useful solution compromises. We show that the approach performs better, with respect to solution quality and/or computation time, than other neural network applications to the VRP presented in the literature. As well, it substantially reduces the gap to classical Operations Research heuristics, specifically on the large VRP instances with time duration constraint.     

Multi-domain collaborative exploration mechanisms for query expansion in an agent-based filtering framework

Novice users often do not have enough domain knowledge to create good queries for searching information on-line. To help alleviate the situation, exploration techniques have been used to increase the diversity of the search results so that not only those explicitly asked will be returned, but also those potentially relevant ones will be returned too. Most existing approaches, such as collaborative filtering, do not allow the level of exploration to be controlled. Consequently, the search results can be very different from what is expected. We propose an exploration strategy that performs intelligent query processing by first searching usable old queries, and then utilising them to adapt the current query, with the hope that the adapted query will be more relevant to the user’s areas of interest. We applied the proposed strategy to the implementation of a personal information assistant (PIA) set up for user evaluation for 3 months. The experimental results showed that the proposed exploration method outperformed collaborative filtering, and mutation and crossover methods by around 25% in terms of the elimination of off-topic results.     

An object-oriented software life cycle of an intelligent tutoring system

Abstract  This paper describes the application of an object-oriented model of life cycle in the development of an intelligent tutoring system for secondary students in the domain of algebraic powers. The system is called EasyMath and has been developed using the Rational Unified Process, which is an object-oriented process proposed for use with the Unified Modelling Language. The Rational Unified Process supports multiple recursions of the phases of the software life cycle. This has been enriched to include empirical studies and formative evaluations appropriate for knowledge-based educational software.     

基于多媒体多智能Agents系统的群体决策支持系统集成化设计研究

分析了Ｄeｓａｎｅｔｉｓ＆Ｇａｌｌｕｐｅ群体决策支持系统（Ｇｒｏｕｐ Ｄｅｃｉｓｉｏｎ Ｓｕｐｐｏｒｔ,简称ＧＤＳＳ）初步设计的通用模式,提出了将多媒体技术、智能Ａｇeｎｔs技术、数据仓库技术Ｉｎｔｅｒｎｅｔ／Ｉｎｔｒａｎｅｔ技术等有机地集成于ＧＤＳＳ的集成化设计方案,并就其关键技术功能结构方案设计进行了研究．     

基于RS理论的过程企业生产工艺数据挖掘

在简要回顾了模糊控制、人工神经网络控制和粗糙控制的基本原理与特点之后,提出了运用RS理论对过程企业生产工艺数据进行挖掘以得到有关生产工艺过程控制规则的方法,用以辅助操作人员不断总结经验,提高操作水平,是上述智能控制方法的极好补充。     

知识获取技术及其在网络智能故障诊断中的应用

基于遗传算法提出了一种新型的机器学习方法,它利用遗传算法的全局寻优手段,为解决知识获取这一瓶颈问题另辟捷径。论述了该方法的原理及其实现过程,并且给出了网络故障诊断应用实例,证明了它的有效性。     

A reactive GRASP and path relinking for a combined production–distribution problem

An NP-hard production–distribution problem for one product over a multi-period horizon is investigated. The aim is to minimize total cost taking production setups, inventory levels and distribution into account. An integer linear model is proposed as a compact problem specification but it cannot be solved to optimality for large instances. Instead of using a classical two-phase approach (production planning and then route construction for each day), metaheuristics that simultaneously tackle production and routing decisions are developed: a GRASP (greedy randomized adaptive search procedure) and two improved versions using either a reactive mechanism or a path-relinking process. These algorithms are evaluated on 90 randomly generated instances with 50, 100 and 200 customers and 20 periods. The results confirm the interest of integrating production and distribution decisions, compared to classical two-phase methods. Moreover, reaction and path-relinking give better results than the GRASP alone.     

压力（位移）自动检测控制器检测单元接口设计

主要研究电液控制放大器模拟量输入通道中,位移传感器检测单元的测量放大电路和各输入信号与智能控制器的接口电路,使控制器的输入与各传感器的输出信息相匹配。     

Information agent technology for the Internet: A survey

The vast amount of heterogeneous information sources available on the Internet demands advanced solutions for acquiring, mediating, and maintaining relevant information for the common user. Intelligent information agents are autonomous computational software entities that are especially meant to (1) provide pro-active resource discovery, (2) resolve information impedance of information consumers and providers, and (3) offer value-added information services and products. These agents are supposed to cope with the difficulties associated with the information overload of the user, preferably just in time.

Based on a systematic classification of intelligent information agents, this paper presents an overview of the basic key enabling technologies needed to build such agents, and respective examples of information agent systems currently deployed on the Internet.