Scheduling Performance Evaluation of Logistics Service Supply Chain Based on the Dynamic Index Weight

Scheduling is crucial to the operation of logistics service supply chain (LSSC), so scientific performance evaluation method is required to evaluate the scheduling performance. Different from general project performance evaluation, scheduling activities are usually continuous and multiperiod. Therefore, the weight of scheduling performance evaluation index is not unchanged, but dynamically varied. In this paper, the factors that influence the scheduling performance are analyzed in three levels which are strategic environment, operating process, and scheduling results. Based on these three levels, the scheduling performance evaluation index system of LSSC is established. In all, a new performance evaluation method proposed based on dynamic index weight will have three innovation points. Firstly, a multiphase dynamic interaction method is introduced to improve the quality of quantification. Secondly, due to the large quantity of second-level indexes and the requirements of dynamic weight adjustment, the maximum attribute deviation method is introduced to determine weight of second-level indexes, which can remove the uncertainty of subjective factors. Thirdly, an adjustment coefficient method based on set-valued statistics is introduced to determine the first-level indexes weight. In the end, an application example from a logistics company in China is given to illustrate the effectiveness of the proposed method

Resource Planning in Engineering Services Firms

We develop a model to enable engineering professional services firms to improve the management of their competitive resources, i.e., skilled engineers, to be better able to respond to customer demand. The model was informed by semistructured interviews with senior executives from engineering, information technology (IT) services and technical consulting firms. As a result, we capture many of the complexities associated with the resource planning process in the professional engineering services sector. In the resulting model, the key attributes of supply, demand, and operations constraints are identified. Based on information obtained from the interviews, a number of test firms are created.We then use these test firms to study the impact of various resource planning policies on firm performance. These policies include the skill mix and profile of skilled employees, limits on the number of concurrent projects to which an employee can be assigned, and policies governing employee cross-training and hiring. The impact of these policies is evaluated in terms of business metrics, such as the project completion rate and net revenue. Finally, our model is extended to capture a multiphase rolling planning horizon, where projects may span multiple phases with the goal of ensuring consistency in employee assignment to projects

Strategic and Tactical Crude Oil Supply Chain: Mathematical Programming Models

Crude oil industry very fast became a strategic industry. Then, optimization of the Crude Oil Supply Chain (COSC) models has created new challenges. This fact motivated me to study the COSC mathematical programming models. We start with a systematic literature review to identify promising avenues. Afterwards, we elaborate three concert models to fill identified gaps in the COSC context, which are (i) joint venture formation, (ii) integrated upstream, and (iii) environmentally conscious design

Portfolio Construction: The Efficient Diversification of Marketing Investments

Efforts in the marketing sciences can be distinguished between the analysis of individual customers and the examination of portfolios of customers, giving scarce theoretical guidance concerning the strategic allocation of promotional investments. Yet, strategic asset allocation is considered in financial economics theory to be the most important set of investment decisions. The problem addressed in this study was the application of strategic asset allocation theory from financial economics to marketing science with the aim of improving the financial results of investment in direct marketing promotions. This research investigated the components of efficient marketing portfolio construction which include multiattribute numerical optimization, stochastic Brownian motion, peer index tracking schemes, and data mining methods to formulate unique investable asset classes. Three outcomes resulted from this study on optimal diversification: (a) reduced saturative promotional activities balancing inefficient advertising cost and enterprise revenue objectives to achieve an investment equilibrium state; (b) the use of utility theory to assist in the lexicographic ordering of goal priorities; and (c) the solution approach to a multiperiod linear goal program with stochastic extensions. A performance test using a large archival set of customer data illustrated the benefits of efficient portfolio construction. The test asset allocation resulted in significantly more reward than that of the benchmark case. The results of this grounded theory study may be of interest to marketing researchers, operations research practitioners, and functional marketing executives. The social change implication is increased efficiency in allocation of large advertising budgets resulting in improved corporate performance

System and Decision Sciences at IIASA 1973-1980

This report contains a brief history of the past achievements of the System and Decision Sciences Area at IIASA, and a summary of its current and future research directions. There is a comprehensive list of the scientific staff of the Area since 1973, together with a list of their publications; abstracts of the most recent reports and biographies of the scholars working in the Area in 1980 are also included

Dynamic Linear Models for the Study of Agricultural Systems

This volume presents five studies for modeling agro-industrial development at a regional and enterprise level with the basic methodological framework of dynamic linear programming. The first two papers focus on methodological problems. Section 1 describes a dynamic linear modeling framework for studying agro-industrial development. The introduction of uncertainties in linear dynamic agricultural models is discussed in Section 2. Concrete modeling projects using dynamic linear programming are reported in the next three papers. A farm level application of dynamic Linear models is presented in Section 3. Section 4 gives an account of the Silistra case study where the dynamic linear model elaborated at IIASA was used as the basic methodology for planning the region's agro-industrial development. Finally, Section 5 describes a dynamic linear water demand model