Determination of recovery effort for a probabilistic recovery system under various inventory control policies

In this study we investigate the desired level of recovery under various inventory control policies when the success of recovery is probabilistic. All the used and returned items go into a recovery process that is modelled as a single stage operation. The recovery effort is represented by the expected time spent for it. The effect of increasing recovery effort on the success probability together with unit cost of the operation is included by assuming general forms of dependencies. Alternative to recovered items, demand is satisfied by brand-new items. Four inventory control policies that differ in timing of and information used in purchasing decision are proposed. The objective is to find the recovery level together with inventory control parameter that minimize the long-run average total cost. A numerical study covering a wide range of system parameters is carried out. Finally computational results are presented with their managerial implications.     

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.     

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。     

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。     

Symptoms of Eating Disorders Among Females in Drug Addiction Treatment

The aim of this study is to measure and describe symptoms of eating disorders among females in treatment for drug addiction in Norway. Previous clinical and epidemiological studies have revealed coprevalence between eating disorders and substance use or abuse. However, few studies have measured eating disorders in drug-using samples and even fewer within the context of drug treatment. In this study, 29 females with drug use disorder in residential treatment were tested with the Eating Disorder Inventory–2. A subgroup of 9 females (31%) with significant symptoms of eating disorders was identified. The characteristics of this group and possible clinical consequences are discussed.     

Population structure and correlation between auxiliary and target variables may affect precision of estimates in forest inventory

Simulations of forest inventory in several populations compared simple random with “quick probability proportional to size” (QPPS) sampling. The latter may be applied in the absence of a list sampling frame and/or prior measurement of the auxiliary variable. The correlation between the auxiliary and target variables required to render QPPS sampling more efficient than simple random sampling varied over the range 0.3–0.6 and was lower when sampling from populations that were skewed to the right. Two possible analytical estimators of the standard error of the estimate of the mean for QPPS sampling were found to be less reliable than bootstrapping.     

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。