Penalty guided genetic search for redundancy optimization in multi-state series-parallel power system

This paper presents a genetic algorithm (GA) for parallel redundancy optimization in series-parallel power systems exhibiting multi-state behavior, optimizing the reliability subject to constraints. The components are binary and chosen from a list of products available in the market, and are being characterized by their feeding capacity, reliability, cost and weight. System reliability is defined as the ability to satisfy consumer demand and is presented as a piecewise cumulative load curve. In GA, to handle infeasible solutions penalty strategies are used. Penalty technique keep a certain amount of infeasible solutions in each generation so as to enforce genetic search towards an optimal solution from sides of, both, feasible and infeasible regions. We here present a dynamic adaptive penalty function which helps the algorithm to search efficiently for optimal/near optimal solution. To evaluate system reliability, a fast procedure, based on universal generating function, is used. An example considering a multi-state series-parallel power system is solved considering both homogeneous and heterogeneous types of redundancy. Also an example considering price discounts is solved. The effectiveness of the penalty function and the proposed algorithm is studied and shown graphically.     

基于两阶段优化算法的神经网络预测模型

采用基于两阶段优化算法(multi-stage optimization approach,MSOA)的GA人工神经网络,将训练集分为两部分,在前一训练集训练后获得的网络基础上使用后一训练集进行进一步的训练获得更为优化的网络结构.针对复杂系统建模输入节点难以确定的问题,提出将其与自组织数据挖掘算法相结合,利用GMDH算法获得神经网络的初始化节点,使用训练好的神经网络模型进行预测.将由此建立的预测模型应用于粮食价格的预测,并进一步探讨了MSOA算法的收敛性问题.结果表明基于GMDH和MSOA的神经网络组合预测模型能较大提高神经网络的全局收敛能力和收敛速度,提高预测精度.     

Inverse Combinatorial Optimization: A Survey on Problems, Methods, and Results

Given a (combinatorial) optimization problem and a feasible solution to it, the corresponding inverse optimization problem is to find a minimal adjustment of the cost function such that the given solution becomes optimum.Several such problems have been studied in the last twelve years. After formalizing the notion of an inverse problem and its variants, we present various methods for solving them. Then we discuss the problems considered in the literature and the results that have been obtained. Finally, we formulate some open problems.     

基于递阶生产系统投入产出模型的企业生产经营决策优化应用的研究

本文基于递阶生产系统投入产出模型,以某锦纶厂为应用背景,在建立销售结构优化模型的基础上,对企业销售结构优化、企业内部潜力挖掘和产品定价等几个方面的经营决策优化问题进行了探讨,并进行了成功的实践。     

新形势下制造业物流体系布局优化研究

制造业物流体系是制造业与物流业协同发展衍生出的新体系模式。当前,我国已经迈入经济转型的攻关期。在这种新形势下,制造业物流发展面临着新的机遇。以沈阳市为例,探讨了物流体系布局优化的方法,并给出了布局优化模型。在阐述沈阳市制造业物流现状及存在问题的基础上,提出了沈阳市制造业物流体系布局优化方法及模型,旨为制造业物流体系的布局优化提供支持和应用参考。     

面向储能的光伏微网成本评价与对策研究

微电网是智能电网的重要组成部分,可以有效协调区域内的电力资源。为研究面向储能的光伏微网电力成本变化情况和优化对策,基于微网多主体结构构建微网电力成本均衡模型,以微网内分布式光伏供应及用户电力需求的统计数据为主要输入对象,并设置变量来区分不同情景下的分布式可再生能源发电量,建立以时间为自变量的微网分布式电力收益函数和用户购电成本函数,刻画微网电力资源调度的动态均衡变化。基于微网电力资源调度实例,发现微网在并网情景下的购电成本小于储能情景下的购电成本（C并=2 033.6元C储=2 633.6元）,且储能情景下购电成本的22.8%都来自储能设施的日折旧费,因此,加大科技研发和增强微网协同管理可以降低微网成本。     

Staff rostering in call centers providing employee transportation

We address the staff rostering problem in call centers with the goal of balancing operational cost, agent satisfaction and customer service objectives. In metropolitan cities such as Istanbul and Mumbai, call centers provide the transportation of their staff so that shuttle costs constitute a significant part of the operational costs. We develop a mixed integer programming model that incorporates the shuttle requirements at the beginning and end of the shifts into the agent-shift assignment decisions, while considering the skill sets of the agents, and other constraints due to workforce regulations and agent preferences. We analyze model solutions for a banking call center under various management priorities to understand the interactions among the conflicting objectives. We show that considering transportation costs as well as agent preferences in agent-shift assignments provides significant benefits in terms of both cost savings and employee satisfaction.     

关于优化齐齐哈尔历史文化资源的思考

历史文化资源是城市特有文化形态的依托和我体。能否挖掘、保护、梳理好历史文化资源，关系到城市优秀历史文化的继承与弘扬，关涉到城市未来的发展与走向。历史文化资源，不但要挖掘、整理、保护，更要优化。优化历史文化资源，就是在文明的大背景下，系统梳理历史文化资源，理清历史发展脉络，理清文明发展足迹，理清优秀历史文化传统，进而树立鲜明的城市文化形象，增强城市文化软实力。     

A harmony search-based memetic optimization model for integrated production and transportation scheduling in MTO manufacturing

This paper investigates an integrated production and transportation scheduling problem in an MTO supply chain. A harmony search-based memetic optimization model is developed to handle this problem, in which certain heuristic procedures are proposed to convert the investigated problem into an order assignment problem. A novel improvisation process is also proposed to improve the optimum-seeking performance. The effectiveness of the proposed model is validated by numerical experiments. The experimental results show that (1) the proposed model can solve the investigated problem effectively and that (2) the proposed memetic optimization process exhibits better optimum-seeking performance than genetic algorithm-based and traditional memetic optimization processes.     

施工企业投标优化的问题与对策

通过对某大型施工企业多个铁路、公路施工项目部的调查，总结了企业当前投标优化方面存在的问题。针对企业以铁路、公路项目为主业的特点，提出了优势项目滚动发展、建立有效激励制度、做好投标准备、优化施工组织设计、应用报价技巧等优化对策。对于施工企业改善市场经营效果，提高中标质量，增加项目盈利有重要的借鉴作用。