MA-15 IFORS 20<strong>11</strong> - Melbourne 1 - Optimality Conditions via Exact Penalty Functions Xiaoqi Yang, Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, mayangxq@polyu.edu.hk, Kaiwen Meng In this paper, we study KKT optimality conditions for constrained nonlinear programming problems and strong and Mordukhovich stationarities for mathematical programs with complementarity constraints using l_p penalty functions, with 0
We study the online version of the classic uniform machine scheduling problem to minimize total weighted completion time with nonpreemptive setting. Using the linear programming based scheduling technique, we present a deterministic online scheduling policy for that model, and derive performance guarantees that is related to the number of machines and the ratio between the largest machine’s speed and the total machine’s speed. Our algorithm naturally extends several approaches to uniform machine scheduling. To the best of our knowledge, it is the first competitive ratio for this problem. 4 - An Equilibrium Model of Distribution Supply Chain Network with Inventory Transshipment Jing Zhou, Management Science and Engineering, Nanjing University, 210093, Nanjing, Jiangsu, China, houcaishen@gmail.com In this paper, an equilibrium model of distribution supply chain network with inventory transshipment was developed based on capacity constraints equilibrium model of supply chain network. The model was calculated by a simple case with two wholesalers, two retailers and two consumers. It confirmed that inventory transshipment would cause an increase in total cost of distribution supply chain. However, the total cost would decrease when increasing the cost of inventory transshipment. To restrain abnormal behaviors, some strategies were suggested to increase the cost of inventory transshipment. � MA-17 <strong>Monday</strong>, <strong>11</strong>:30-13:00 Meeting Room 214 Robust Multi Criteria Decision Analysis Stream: Multicriteria Decision Analysis and Multiobjective Optimisation Invited session Chair: Jutta Geldermann, Professur für Produktion und Logistik, Universität Göttingen, Platz der Göttinger Sieben 3, D-37073, Göttingen, Germany, geldermann@wiwi.uni-goettingen.de 1 - Evaluation based Resource Allocation to Improve Security in Container Line Supply Chain Dawei Tang, Manchester Business School, M13 9UR, Manchester, United Kingdom, dawei.tang.wh@googlemail.com, Dong-Ling Xu, Shan-Lin Yang, Jian-Bo Yang Container Line Supply Chain (CLSC) is a dominant yet high vulnerable way to transport cargo globally, whilst resources to improve its security are always limited. To improve CLSC security efficiently, a model is developed to allocate resources optimally for CLSC. Different from other Resource Allocation (RA) models, the model proposed has 2 major features: 1) resources are allocated based on security evaluation, thus areas with lower security have higher priority to get resources; 2) the proposed model can handle imprecise, uncertain and semi-structured information involved in RA processes. 2 - Stochastic and Robust Multicriteria Decision Support for Supply Planning of Renewable Resources Susanne Wiedenmann, Professur für Produktion und Logistik, Universität Göttingen, Platz der Göttinger Sieben 3, 37073, Göttingen, Germany, susanne.wiedenmann@wiwi.uni-goettingen.de, Sven Krumke, Jutta Geldermann Supply planning for the industrial use of renewable resources confronts the decision maker with specific challenges. We study models and policies for coping with incomplete and uncertain information and discuss various ways to cope with the uncertainty. Since this involves a couple of conflicting goals which cannot be scalarized in a straightforward way, this naturally leads to a multicriteria optimization problem. We analyze this problem from the viewpoints of robust, stochastic and online optimization and provide computational results. 3 - Application of Non-Linear Optimization for the Determination of Optimal Plant Setups for Biofuel Production Lars-Peter Lauven, Chair of Production and Logistics, Georg-August-Universitaet Goettingen, Platz der Goettinger Sieben 3, 37073, Goettingen, Germany, llauven@gwdg.de, Jutta Geldermann IFORS 20<strong>11</strong> - Melbourne MA-18 Second Generation biofuels are often based on complex synthesis reactions with numerous products. Superlinearly rising specific transportation costs for large biofuel plants using biomass as input material counteract the desirable effects of sublinearly rising economies of scale. Modeling these two drivers of biofuel production costs is necessary to determine an optimal choice of plant size and product upgrading setup. The resulting non-linear optimization problem is solved using the CONOPT solver, which is based on the Generalized Reduced Gradient algorithm. � MA-18 <strong>Monday</strong>, <strong>11</strong>:30-13:00 Meeting Room 215 Applications of DEA in Firms and Industries Stream: Data Envelopment Analysis Invited session Chair: Antonio Perrelli, Finance and Economics Dept., ELETROBRAS Chesf, R. Carlos Pereira Falcão 743 ap 103, 51021350, Recife, PE, Brazil, antonioperrelli@hotmail.com 1 - Forecasting Electric Energy Consumption and Benchmarking Performance of Selected Buildings in the University of Santo Tomas Oliver Gagarin, Facilities Management Office, University of Santo Tomas, Espana, 1008, Manila, Philippines, orgagarin@mnl.ust.edu.ph, Nancy Eleria The electric energy consumption (EEC) is significant in the building past and future performances. Regression analysis and ANN are used to determine the effects of physical and climatic variables in EEC. The building performances are determined by Multi-Stage DEA. It has identified that the building size, number of enrolled students, building age, and peak-load time are the physical factors affecting EEC. The study concluded that some buildings are technically inefficient because they are having EEC more than what their age and peak-load time would require in a monthly operation. 2 - The Application of Improved DEA Model in Evaluation of China’s Production Comprehensive Efficiency Yuquan Cui, School of Mathematics, Shandong University, Shan Da Nan Lu Number 27, 250100, Jinan, Shandong, China, cuiyq@sdu.edu.cn In this paper, we improved DEA model. According to the function of output data and input data, we determine the form and number of input variables. If input variables are too many, we can use principal component analysis to reduce the dimensions, and then we use the improved DEA model to calculate. We use the improved DEA model to evaluate and analyze the efficiency of the production environment in China in recent years. Actual evaluation results are excellent agreement with the actual situation. 3 - The Determinants of Firms’ Efficiency in the International Textile and Clothing Industry Magdalena Kapelko, Department of Business Administration, Universidad Carlos III de Madrid, Calle Madrid 126, Office 7.0.56, 28903, Getafe (Madrid), Spain, magdalena.kapelko@gmail.com This study examines the factors that can explain efficiency of international textile and clothing industry. We rely on the original database of 5477 observations for the firms that operated in different world regions from 1995 to 2004. We use truncated regression with bootstrap to infer on the relationship of DEA efficiency to some factors that based on the theory are related to efficiency. Our evidence shows that efficiency is positively associated with intangibles, size, textile sector and economic development. Other variables such as leverage and economic integration contribute negatively. 4 - The Use of Data Envelopment Analysis as a Regulation Tool for the Energy Transmission Sector in Brazil Antonio Perrelli, Finance and Economics Dept., ELETROBRAS Chesf, R. Carlos Pereira Falcão 743 ap 103, 51021350, Recife, PE, Brazil, antonioperrelli@hotmail.com 9
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We look into project scheduling wit
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Airline Applications Invited Matthi
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Network Optimisation and Telecommun
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