Algorithm portfolios for logistics optimization considering stochastic demands and mobility allowance

The vehicle routing problem with stochastic demand (VRPSD) is a well known NP-hard problem. The uncharacteristic behaviour associated with the problem enhances the computational efforts required to obtain a feasible and near-optimal solution. This paper proposes an algorithm portfolio methodology based on evolutionary algorithms, which takes into account the stochastic nature of customer demand to solve this computationally complex problem. These problems are well known to have computationally complex objective functions, which make their solutions hard to find, particularly when problem instances of large dimensions are considered. Of particular importance in such situations is the timeliness of the solution. For example, Apple was forced to delay their shipments of iPads internationally due to unprecedented demand and issues with their delivery systems in Samsung Electronics and Seiko Epson. Such examples illustrate the importance of stochastic customer demands and the timing of delivery. Moreover, most of the evolutionary algorithms, known for providing computationally efficient solutions, are unable to always provide optimal or near optimal solutions to all the VRPSD instances within allocated time interval. This is due to the characteristic variations in the computational time taken by evolutionary algorithms for same or varying size of the VRPSD instances. Therefore, this paper presents portfolios of different evolutionary algorithms to reduce the computational time taken to resolve the VRPSD. Moreover, an innovative concept of the mobility allowance (MA) in landmoves based on the levy’s distribution function has been introduced to cope with real situations existing in vehicle routing problems. The proposed portfolio approach has been evaluated for the varying instances of the VRPSD. Four of the existing metaheuristics including Genetic Algorithm (GA), Simulated Annealing (SA), Artificial Immune System (AIS), TABU Search (TS) along with new neighbourhood search, are incorporated in the portfolios. Experiments have been performed on varying dimensions of the VRPSD instances to validate the different properties of the algorithm portfolio. An illustrative example is presented to show that the set of metaheuristics allocated to certain number of processors (i.e. algorithm portfolio) performed better than their individual metaheuristics.     

区域竞争力内涵的多元化认知与辨析

在梳理了有关区域竞争力涵义的几种比较有代表性的观点：财富创造说,可持续发展能力说,经济实力说,资源配置说,综合能力说,因素说以及其他观点的基础上,认为,区域竞争力是一个区域在发展过程中同其他区域竞争过程中所表现出来的对资源的吸引争夺能力以及通过对已有资源的优化和合理配置,使得本区域能够得到持续、综合、协调的发展,不断形成区域竞争优势的能力。区域竞争力是区域多种能力合成的结果,区域竞争力的强弱将直接影响到区经济发展的后劲。区域竞争力的核心是创造竞争优势。     

Demand chain alignment competence — delivering value through product life cycle management

This paper endorses demand chain alignment as a competence that supports effective product life cycle (PLC) management. Demand chain alignment integrates the demand creation (historic domain of marketing) and demand fulfilment processes (domain of supply chain management), to develop and to deliver products that convey superior customer value while deploying resources efficiently. So far, the relationship between demand chain alignment and PLC management has only been addressed from an operations and demand/supply chain perspective, but not from a marketing perspective. Three research propositions, on the relationship between both concepts, are derived from a literature review and applied to a case study from a global player in the tobacco industry. The findings do not support the current view that the product life cycle is a market-oriented classification variable for demand chain strategies. Instead, demand chain alignment needs to link customer needs-based segments with the supply chain. Moreover, PLC management and demand chain alignment have a mutually reinforcing relationship, in which PLC management can facilitate the competence development, ensures a dynamic perspective and, at the same time, benefits from aligned demand creation and fulfilment processes. Based on the findings, a model integrating demand chain alignment and PLC management is proposed.     

Exploring the learning problems and resource usage of undergraduate industrial design students in design studio courses

Design is a powerful weapon for modern companies so it is important to have excellent designers in the industry. The purpose of this study is to explore the learning problems and the resources that students use to overcome problems in undergraduate industrial design studio courses. A survey with open-type questions was conducted to collect data. Participants in this study were 189 undergraduate industrial design students from three universities, and two coding schema were formulated for analysing the data. The results demonstrated that the most difficult design tasks included concept generation, design presentation, and design research. The learning resources used to solve the learning problems included four categories: people, object, method, and environment. This information will increase the understanding of the learning process of students and provide a reference for teaching and the setting of learning resources in industrial design education.     

Price behavior in tight oligopoly

The study examines price behavior in tight oligopoly. The investigation proceeds from the premise that tacit cooperation is the rational response of firms comprising tight oligopoly. The study’s thesis is that cooperative conduct in tight oligopoly will reflect one of two general pricing patterns: (1) shared monopoly pricing, or (2) mark-up pricing. A unique empirical test of this dual price hypotheses is developed. The test focuses on the nature of price responses to cost and demand changes as reflected in a price equation that is estimated for each of fifty four-digit SIC industries. The study’s results indicate infrequent, but still notable, instances of shared monopoly pricing. More common is evidence of mark-up pricing, a general category within which demand proved to be significant in roughly half of the industries examined. Theoretical implications of these findings are discussed.     

Downstream mergers in vertically related markets with capacity constraints

Motivated by a recent merger proposal in the French outdoor advertising market, we develop a model in which firms are initially endowed with some advertising capacities and compete on two fronts. First, firms compete to acquire additional advertising capacities on an upstream market; a first stage modeled as a second-price auction with externalities. Second, those firms, privately informed on their own costs, use their capacities on the downstream market to supply advertisers whose demand is random; a second stage modeled by means of mechanism design techniques. We study the linkages between the equilibrium outcomes on both markets. When a firm is endowed with more initial capacity, through the acquisition of a competitor for instance, whether it becomes more or less eager to acquire extra capacity on the upstream market depends a priori on fine details of the downstream market. Under reasonable choices of functional forms, we demonstrate that a downstream merger does not create any bias in the upstream market towards the already dominant firm.     

Stochastic single-source capacitated facility location model with service level requirements

A stochastic version of single-source capacitated facility location problem is considered. A set of capacitated facilities is to be selected to provide service to demand points with stochastic demand at the minimal total cost. The facilities have service level requirements modeled by chance constraints. For Poisson demand, the problem is proved equivalent to a known solvable deterministic problem. For Normally distributed demand, it is equivalent to a deterministic mixed integer non-linear programming problem. A hybrid heuristic of Lagrangean relaxation with a single-customer-multi-exchange heuristic is embedded within a branch-and-bound framework to find upper and lower bounds for this problem. From test instances created from benchmark problems (10–20 facilities and 50 demand nodes) and real-life data on the deterministic problem, the gap between the bounds is within 6.5% with an average of 2.5%.     

Servitization,digitization and supply chain interdependency

This study draws on literature at the intersection of servitization, digital business models and supply chain management. Work empirically explores how digital disruption has affected Business-to-Business (B2B) interdependencies. Dematerialization of physical products is transforming the way firms are positioned in the supply chain due to a reduction in production and transport costs and the different ways business engage with customers. Specifically, we propose that these new market conditions can empower downstream firms. We further propose that upstream firms can still capture additional value through digital service if their servitized offer includes difficult to imitate elements. The context of the analysis is the publishing industry. The Payment Card method employed is used to test UK and US consumer's perceptions of digital formats (eBooks) and assess their willingness to pay in relation to printed formats. The method undertaken enables us to elicit aggregated consumer demand for eBooks which in turn identifies optimal pricing strategies for the digital services. Analysis demonstrates that during digital servitization upstream firms should seek to deploy unique resources to ensure their strategic position in the supply chain is not diminished.     

A local search algorithm for the optimization of the stochastic economic lot scheduling problem

This paper describes a model for the stochastic economic lot scheduling problem (SELSP) and a Local Search heuristic to find close to optimal solutions to this model. The SELSP considers multiple products, which have to be scheduled on a single facility with limited capacity and significant setup times and costs. The demand is modeled as a stationary compound renewal process. The objective is to find a schedule that minimizes the long-run average costs for setups and inventories while satisfying a given fill rate. We use a cyclic scheduling approach in which the individual cycle time of each product is a multiple of some basic period (fundamental cycle).For the deterministic version of the SELSP, efficient heuristics have been developed which guarantee the feasibility of the solution by adding an additional constraint to the problem. In our case this is not sufficient, because for the calculation of the average inventory levels and fill rates we need to develop a schedule with detailed timing of the lots. We present an efficient heuristic for this scheduling problem, which can also be used to check the feasibility of the solution. Thereby, the most time-consuming step (the calculation of average inventory levels and fill rates) is only performed for a limited set of candidates.The algorithm was tested on deterministic benchmark problems from literature and on a large set of stochastic instances. We report on the performance of the heuristic in both cases and try to identify the main factors influencing the objective.     

The impact of the Medicare Rural Hospital Flexibility Program on patient choice

This paper seeks to understand the impact of the Medicare Rural Hospital Flexibility (Flex) Program on rural resident hospital choice. The program created a new class of hospital, the Critical Access Hospital (CAH), which receives more generous reimbursement in return for limiting its beds and services. The program's goal is to maintain access to hospital care. Estimates from a patient choice model show that patient utility from visiting a hospital was negatively affected by conversion. While the lower bed capacity appears to play a minor role, the reduction in services results in a 28% drop in admission rates.     

基于天气雷达估测降雨数据的节水灌溉系统设计与实现

农业用水在水资源的应用中占有很大比例,为节约农田灌溉用水,以满足农作物生长需求为前提,提出了一种基于天气雷达估测降雨技术的农田灌溉方法。结合概念模型预报技术和交叉相关法,对降雨进行临近预报,利用未来时间的降雨量对农田作物的需水量进行合理补充,并通过检测装置获取土壤含水量,计算出农田需水量,实现对检测区域作物的定量灌溉。系统试运行结果显示,在短时间内,采用天气雷达估测技术预测的结果与地面雨量计观测的降水结果在误差允许的范围内保持一致,验证了方法的准确性。该技术方案将天气雷达估测降雨技术与数据采集技术相结合,利用现代农业科学技术及设备,充分应用了自然降雨资源,在现有的农业技术水平基础上,既满足了农作物自身的生长需求,又避免了过量灌溉等问题,对中国水资源在农田灌溉中的合理应用有着一定的指导意义。     

Establishing Maintenance Resource Levels Using Selective Maintenance

We address the performance of a repairable system that is required to perform a sequence of equally spaced, identical missions with breaks between missions. The system is series-parallel in structure, and component repair can only be performed during breaks between missions. Due to limitations on maintenance resources, it may be impossible to make all necessary repairs before the next mission. Such situations require the use of selective maintenance, the process of identifying the subset of maintenance actions to perform from a set of desirable maintenance actions. We build upon previous research in selective maintenance by addressing decisions related to establishing capacities for the limited maintenance resources. We model mission-to-mission changes in maintenance resource capacity, and we develop a methodology for establishing constant resource capacities for a sequence of missions. Finally, we develop a methodology for integrating redundancy allocation and maintenance resource allocation decisions.     

Leveraging the benefits of exploratory learning and exploitative learning in NPD: the role of innovation field orientation

Scholars have increasingly noted that firm-level capabilities may be crucial for resolving the dilemmas resulting from either high exploratory or high exploitative learning. However, our current understanding of this issue remains limited. Innovation field orientation is a firm-level capability to strategically structure dispersed innovation efforts and reconfigure resources on them, and may help a firm leverage the benefits of distinctive learning strategies. Based on this idea, this paper investigates innovation field orientation and examines how its capacities (the specification, establishment of focus areas, and stimulation of synergies) influence the performance of high exploratory/exploitative learning. Our findings suggest that the capacities of innovation field orientation moderate the effects of exploratory and exploitative learning on new product program performance, and clarify how innovation field orientation enables organization to leverage the benefits of high exploratory/exploitative learning and address their disadvantages.     

A mixed spectrum management framework for the future wireless service based on techno-economic analysis: The Korean spectrum policy study

The evolution of radio technology and various services has increased the world's dependence on wireless communications. The demand for and value of spectrum resources therefore are also increasing. Spectrum efficiency is the most important factor in managing spectrum scarcity. However, under the current spectrum management approach, it is difficult to adopt innovative technologies that improve spectrum efficiency and flexible usage in the current dynamic wireless market. Recently, there have been several approaches to improve efficient use of spectrum resources, and each approach has its own advantages and disadvantages. Therefore, this research first discusses current issues and analyzes relative social welfare based on the different characteristics of technology and market conditions to compare various attributes of each approach. Based on the techno-economic simulation results, this paper introduces a mixed spectrum management framework for the future wireless service and support policy makers’ decision making. Furthermore, the mixed spectrum policy to spectrum management in Korea is proposed to find a more realistic and efficient spectrum management policy.     

Enhancing the EU’s Energy Supply Security—An Evaluation of the Nabucco Project and an Introduction to Its Open Season Capacity Allocation Process

The Russian dominance of the European Union (EU)’s natural gas supplies has put the independence of the EU at risk. This paper presents an evaluation of the Nabucco gas pipeline project—considered by some to be the most economical link to new natural gas sources—to determine whether it would help the EU to diversify its gas supplies in a cost-effective way, thus improving its energy supply security in future years. Furthermore, an introduction to the Nabucco Open Season Capacity Allocation Process is given. Applying empirical methods and competitive pipeline benchmarking analysis, three hypotheses related to the Nabucco natural experiment are evaluated: while hypothesis (1) focuses on the strength of demand for the Nabucco pipeline transportation capacities, hypotheses (2) and (3) examine fair usage rights and overall cost effectiveness of this project. Empirical results show that, due to the EU’s increasing long-term gas demand and decreasing indigenous production, there is a strong demand for the Nabucco gas pipeline by gas shippers. Furthermore, the empirical survey reveals that Nabucco provides a fair capacity allocation of fifty percent to third party shippers. Finally, competitive benchmarking shows Nabucco is indeed a cost-effective new pipeline and a link to fresh natural gas sources for Europe. Based on these results, it is anticipated that “Nabucco” will not only remain the name of a famous opera, but will also become the term associated with one of the most successful energy projects in Europe.     

The selected determinants of manufacturing postponement within supply chain context: An international study

Modern supply chains focus on an ultimate consumer satisfaction and often require essential dynamic reconfiguration. Manufacturing companies constitute important central nodes in supply chains, where almost all physical flows are concentrated.Postponement is the operating concept, which aims at delaying activities until a customer’s order has been received. The growth of interest in the postponement concept partially results from the increased demand for customized products.Data for the analysis has been collected through the survey carried out by researchers in several countries. The main research instrument used for this research was a questionnaire developed by the Global Manufacturing Research Group (GMRG). The conclusions formulated on the basis of data analysis proved that market and demand characteristics do not seem to be important for the choice between postponement and speculation strategy. The research showed that assembly postponement depends mostly on managerial decisions about the goals of company and the level of acceptance of an assembly postponement strategy on the market. Full postponement strategy is dictated mainly by the level of product customization and capacities of manufacturing and logistics systems. Production postponement has to be accepted on the market and should be associated with excellent forecasting techniques.     

Industrial design students’ perceptions towards a career in user experience field in Turkey

International Journal of Technology and Design Education - The rapid growth of the user experience (UX) field has brought efforts to meet the increasing demand for specialists by welcoming...     

Social relationship cycle for managing small intermediary businesses: Evidences from India

Small businesses in emerging markets face several challenges that are difficult for individual firms to meet on their own, and thus require creative collaboration with other businesses. Using in-depth interview-based exploratory study and the premise of social exchange and dynamic capabilities, we theorize that small businesses engage in a cyclical process with the manufacturer firm. It involves allowing products to be dumped (i.e., ‘Dumping’) in certain situations, while on other occasions providing a cooling-off period (i.e., ‘Releasing’). Based on behavioral learning, we further argue that this Dumping-Releasing cycle is a perpetuating managerial action, which managers alter across size and location of the small firm, resulting in overall superior performance for the manufacturer as well as the small firms. The hypotheses of this model were tested using 34,434 purchase instances over a 92-week period gathered from 2167 small businesses in India. How the study contributes to theory and practice, and potential research opportunities is discussed.     

Integration erneuerbarer Energien in die deutsche Stromversorgung im Zeitraum 2015�C2020 mit Ausblick auf 2025

The dena grid study II examines the integration of renewable energies into Germany??s electricity supply up to the year 2020 and gives a qualified outlook up to 2025. The study develops geographically differentiated scenarios for installed wind power capacity, on the basis of which time series of the wind power feed-in into high and extra high voltage nodes and offshore wind farms are generated. Future requirements for the transmission grid and grid extension options are analysed. Opportunities to introduce more flexibility in the power system in terms of supply and demand are examined. The study gives a conceptual perspective of the need for grid extension in inner Germany in order to fully integrate renewable energies, whilst operating power stations at optimum cost and exchanging electricity with other countries in response to market demands within the scope of the specified transmission capacities.     

Residual demand estimation for market delineation: Complications and limitations

To shed some light on market delineation in an antitrust context, many economists are turning to estimates of residual demand elasticities. Recent papers have drawn attention to the importance of demand curve in market delineation and explained how they can be estimated. This paper shows that there are many complications and limitations of the approach. The relationship between the residual demand elasticity and the scope of the relevant market is complicated and depends on behavioral assumptions. The residual demand elasticity that can be estimated is not the one on which market delineation turns. The estimation of residual demand elasticities can be very difficult because of the complex dynamics of consumer behavior. Finally, residual demand estimators are likely to have a high variance because of instrument problems and this is likely to lead to widely varying estimates depending on specification choices.