Pub Date : 2007-11-19DOI: 10.1109/SOLI.2007.4383887
Weiguo Liu, Shi Zhong, Mayank Chaudhary, S. Kapur
Like any marketing campaigns, online advertisement campaigns need to be monitored, analyzed and optimized. It is more so for online campaigns because online advertisements are usually sold in auction style. Prices can change very dynamically; the creatives, the landing pages and the targeting profiles can all be changed frequently to improve the effectiveness of a campaign. Also, the effectiveness can be measured almost instantly, usually in terms of click through rate and/or the acquisition/conversion rate. It raises many challenging problems in forecasting, data mining and optimization and entails an optimization system for any serious advertisers, publishers or ad networks.
{"title":"Online Advertisement Campaign Optimization","authors":"Weiguo Liu, Shi Zhong, Mayank Chaudhary, S. Kapur","doi":"10.1109/SOLI.2007.4383887","DOIUrl":"https://doi.org/10.1109/SOLI.2007.4383887","url":null,"abstract":"Like any marketing campaigns, online advertisement campaigns need to be monitored, analyzed and optimized. It is more so for online campaigns because online advertisements are usually sold in auction style. Prices can change very dynamically; the creatives, the landing pages and the targeting profiles can all be changed frequently to improve the effectiveness of a campaign. Also, the effectiveness can be measured almost instantly, usually in terms of click through rate and/or the acquisition/conversion rate. It raises many challenging problems in forecasting, data mining and optimization and entails an optimization system for any serious advertisers, publishers or ad networks.","PeriodicalId":154053,"journal":{"name":"2007 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121015410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-19DOI: 10.1109/SOLI.2007.4383895
S. Benedict, V. Vasudevan
Grid computing environment involves all kind of resources namely network, software, data, storage and processing units, evolving towards Global computing to solve a single large problem using Grid scheduling architecture that addresses the interaction between the resource management and data management In this paper, two diferent approaches have been proposed to solve Grid scheduling problem with the objectives of maximizing the Job completion ratio (JCR) and minimizing the lateness. A population based evolutionary algorithm that involves evolution during the search process and a single point local search meta-heuristics that work on a single solution called as hybrid evolutionary algorithm. A Threshold accepting algorithm (TA) proposed is a single point local search meta-heuristic. Proposed algorithms are evaluated and the experimental results are presented for comparison.
{"title":"Scheduling of scientific workflows using Threshold accepting algorithm for Computational Grids","authors":"S. Benedict, V. Vasudevan","doi":"10.1109/SOLI.2007.4383895","DOIUrl":"https://doi.org/10.1109/SOLI.2007.4383895","url":null,"abstract":"Grid computing environment involves all kind of resources namely network, software, data, storage and processing units, evolving towards Global computing to solve a single large problem using Grid scheduling architecture that addresses the interaction between the resource management and data management In this paper, two diferent approaches have been proposed to solve Grid scheduling problem with the objectives of maximizing the Job completion ratio (JCR) and minimizing the lateness. A population based evolutionary algorithm that involves evolution during the search process and a single point local search meta-heuristics that work on a single solution called as hybrid evolutionary algorithm. A Threshold accepting algorithm (TA) proposed is a single point local search meta-heuristic. Proposed algorithms are evaluated and the experimental results are presented for comparison.","PeriodicalId":154053,"journal":{"name":"2007 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122000183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-19DOI: 10.1109/SOLI.2007.4383928
M. Aliabadi
The main objective of the supply chain manager is global optimization through the chain. In this paper, for the first time, the different approaches to prevent or reduce just the inflated orders as an inefficeincy in a supply chain are studied. The main effect of inflated orders in the supply chain is variability in demands. This causes other negative impacts on the supply chain performance for upstream stages. In order to implementation of these approaches be effective, the chosen strategy(ies) must be in place dominantely.
{"title":"Supply chain optimization by reducing and preventing inflated orders","authors":"M. Aliabadi","doi":"10.1109/SOLI.2007.4383928","DOIUrl":"https://doi.org/10.1109/SOLI.2007.4383928","url":null,"abstract":"The main objective of the supply chain manager is global optimization through the chain. In this paper, for the first time, the different approaches to prevent or reduce just the inflated orders as an inefficeincy in a supply chain are studied. The main effect of inflated orders in the supply chain is variability in demands. This causes other negative impacts on the supply chain performance for upstream stages. In order to implementation of these approaches be effective, the chosen strategy(ies) must be in place dominantely.","PeriodicalId":154053,"journal":{"name":"2007 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124781697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-19DOI: 10.1109/SOLI.2007.4383930
Da Shimin, Shen Huizhang, Liu Hong
Recently the research on the crisis management and emergency decision making, especially the decision support method, shows its importance. Initiated by researching on the characteristics of EDM for crisis, this paper proposes a novel iterative decision process model based on Case-based Reasoning (CBR) and Rule-based Reasoning (RBR) for EDM. Using CBR in EDM process can make full use of the previous experiences. Using RBR can support CBR to revise and reuse the similar historical cases. At the same time, an iterative model will satisfy the requirement of the dynamically evolutionary process of crisis. Hence, the proposed model can help identifying EDM's objectives, reducing the difficulty and blindness of EDM, and improving the effectiveness and efficiency of EDM process.
{"title":"Research on Case-Based Reasoning Combined with Rule-Based Reasoning for Emergency","authors":"Da Shimin, Shen Huizhang, Liu Hong","doi":"10.1109/SOLI.2007.4383930","DOIUrl":"https://doi.org/10.1109/SOLI.2007.4383930","url":null,"abstract":"Recently the research on the crisis management and emergency decision making, especially the decision support method, shows its importance. Initiated by researching on the characteristics of EDM for crisis, this paper proposes a novel iterative decision process model based on Case-based Reasoning (CBR) and Rule-based Reasoning (RBR) for EDM. Using CBR in EDM process can make full use of the previous experiences. Using RBR can support CBR to revise and reuse the similar historical cases. At the same time, an iterative model will satisfy the requirement of the dynamically evolutionary process of crisis. Hence, the proposed model can help identifying EDM's objectives, reducing the difficulty and blindness of EDM, and improving the effectiveness and efficiency of EDM process.","PeriodicalId":154053,"journal":{"name":"2007 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"1981 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130337214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-19DOI: 10.1109/SOLI.2007.4383869
Christina Aperjis, R. Strong
We study a single period supply chain model with deterministic demand at the destination and multiple paths through which supplies can be sent. Each path may fail independently. When a path fails, the supply that is sent through that path does not arrive at the destination. We wish to minimize the expected shortage, but also minimize the total supply that is used. We investigate the behavior of various heuristics, deriving some general rules for making good choices and proving an advantage to complex optimization techniques over simple heuristics. We show that when multiple paths have the same characteristics, the optimal solution can be computed significantly faster.
{"title":"Optimization with Conflicting Objectives in Logistic Services","authors":"Christina Aperjis, R. Strong","doi":"10.1109/SOLI.2007.4383869","DOIUrl":"https://doi.org/10.1109/SOLI.2007.4383869","url":null,"abstract":"We study a single period supply chain model with deterministic demand at the destination and multiple paths through which supplies can be sent. Each path may fail independently. When a path fails, the supply that is sent through that path does not arrive at the destination. We wish to minimize the expected shortage, but also minimize the total supply that is used. We investigate the behavior of various heuristics, deriving some general rules for making good choices and proving an advantage to complex optimization techniques over simple heuristics. We show that when multiple paths have the same characteristics, the optimal solution can be computed significantly faster.","PeriodicalId":154053,"journal":{"name":"2007 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129661324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-19DOI: 10.1109/SOLI.2007.4383946
S. Wasserkrug, Shai Taub, Sergey Zeltyn, Dagan Gilat, Vladimir Lipets, Zohar Feldman, A. Mandelbaum
Outsourcing IT support of an enterprise requires that third level IT support is provided as a service by the outsourcer. Although there is a large body of existing work regarding demand forecasting and shift schedule creation for various domains such as call centers, very little work exists for third level IT support. Moreover, there is a significant difference between such support and other types of services. As a result, current best practices for scheduling such work are not based on demand, but rather, on primitive rules of thumb. Due to the increasing number of people providing such support, theory and practice is sorely needed for scheduling third level support shifts according to actual demand. We discuss the issues associated with forecasting and scheduling such work. We also present an end-to-end methodology for forecasting and scheduling this type of work. We discuss this methodology and subsequent results in the context of a specific case study in which this methodology demonstrated significant potential savings in terms of manpower resources.
{"title":"Shift Scheduling for Third Level IT Support: Challenges, Models and Case Study","authors":"S. Wasserkrug, Shai Taub, Sergey Zeltyn, Dagan Gilat, Vladimir Lipets, Zohar Feldman, A. Mandelbaum","doi":"10.1109/SOLI.2007.4383946","DOIUrl":"https://doi.org/10.1109/SOLI.2007.4383946","url":null,"abstract":"Outsourcing IT support of an enterprise requires that third level IT support is provided as a service by the outsourcer. Although there is a large body of existing work regarding demand forecasting and shift schedule creation for various domains such as call centers, very little work exists for third level IT support. Moreover, there is a significant difference between such support and other types of services. As a result, current best practices for scheduling such work are not based on demand, but rather, on primitive rules of thumb. Due to the increasing number of people providing such support, theory and practice is sorely needed for scheduling third level support shifts according to actual demand. We discuss the issues associated with forecasting and scheduling such work. We also present an end-to-end methodology for forecasting and scheduling this type of work. We discuss this methodology and subsequent results in the context of a specific case study in which this methodology demonstrated significant potential savings in terms of manpower resources.","PeriodicalId":154053,"journal":{"name":"2007 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134153532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-19DOI: 10.1109/SOLI.2007.4383961
S. K. Moon, J. Sim, Jun Shu, T. Simpson
The objective in this paper is to introduce a new methodology for strategic module sharing in service family design using game theory to model situations involving uncertain market environments. We extend concepts from platform-based product family design to develop a methodology for module-based service family design. A module selection problem is considered as a strategic game with incomplete information that is described by services' market share ratios and customer's preferences. We employ a Bayesian game to model uncertainty situations regarding market environments and determine strategic equilibrium solutions for selecting modules for the service family being designed. To demonstrate implementation of the proposed Bayesian game, we use a case study involving a family of banking services.
{"title":"Strategic Module Sharing for Customized Service Family Design using a Bayesian Game","authors":"S. K. Moon, J. Sim, Jun Shu, T. Simpson","doi":"10.1109/SOLI.2007.4383961","DOIUrl":"https://doi.org/10.1109/SOLI.2007.4383961","url":null,"abstract":"The objective in this paper is to introduce a new methodology for strategic module sharing in service family design using game theory to model situations involving uncertain market environments. We extend concepts from platform-based product family design to develop a methodology for module-based service family design. A module selection problem is considered as a strategic game with incomplete information that is described by services' market share ratios and customer's preferences. We employ a Bayesian game to model uncertainty situations regarding market environments and determine strategic equilibrium solutions for selecting modules for the service family being designed. To demonstrate implementation of the proposed Bayesian game, we use a case study involving a family of banking services.","PeriodicalId":154053,"journal":{"name":"2007 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132745488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-19DOI: 10.1109/SOLI.2007.4383904
Emre Emil, E. L. Ormeci, F. Salman
Workforce plans in call centers, mostly working 24 hours a day and 7 days a week, have to satisfy both customer service levels and personnel constraints. Moreover, in large metropolitans such as Istanbul, call centers provide the transportation of the staff, so that shuttle costs constitute a major part of the total operational costs. We present a mathematical model which minimizes the transportation costs while satisfying service level and personnel constraints. We test our model with data from call centers.
{"title":"Shift Scheduling in Call Centers with Multiple Skill Sets and Transportation Costs","authors":"Emre Emil, E. L. Ormeci, F. Salman","doi":"10.1109/SOLI.2007.4383904","DOIUrl":"https://doi.org/10.1109/SOLI.2007.4383904","url":null,"abstract":"Workforce plans in call centers, mostly working 24 hours a day and 7 days a week, have to satisfy both customer service levels and personnel constraints. Moreover, in large metropolitans such as Istanbul, call centers provide the transportation of the staff, so that shuttle costs constitute a major part of the total operational costs. We present a mathematical model which minimizes the transportation costs while satisfying service level and personnel constraints. We test our model with data from call centers.","PeriodicalId":154053,"journal":{"name":"2007 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132832237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-19DOI: 10.1109/SOLI.2007.4383876
A. Aparna
Just-in-Time is one of the many improvement techniques that is in vogue such as World Class Manufacturing, Total Quality Management (TQM). The principle feature of JIT approach concerns the management of inventories. It aims to create a zero or low inventory operating system. The primary objective quality and productivity through the elimination of waste. Waste is defined as anything other than the minimum amounts of equipment, materials and workers that are absolutely essential for production. Today, a level of interest has been exhibited to the models pertaining to sales, forecasting and inventory control. Most of the inventory problems assume a given price structure and very less has been researched on the relationship between the two. Here, in this paper, inventory problem has been studied under the pricing structure for a Just-in-Time (JIT) system. The supplier offers the buyer a price discount, which the buyer finds beneficial to him and hence, orders more frequently. This allows both the buyer and the supplier to have less amount of inventory and thus, both minimize the cost. An analysis of how the supplier structures the terms and conditions of an optimal quantity schedule is discussed here.
{"title":"A Quantity Discount Pricing Model to Increase Vendor Profits in a Just - in - Time (JIT) Environment","authors":"A. Aparna","doi":"10.1109/SOLI.2007.4383876","DOIUrl":"https://doi.org/10.1109/SOLI.2007.4383876","url":null,"abstract":"Just-in-Time is one of the many improvement techniques that is in vogue such as World Class Manufacturing, Total Quality Management (TQM). The principle feature of JIT approach concerns the management of inventories. It aims to create a zero or low inventory operating system. The primary objective quality and productivity through the elimination of waste. Waste is defined as anything other than the minimum amounts of equipment, materials and workers that are absolutely essential for production. Today, a level of interest has been exhibited to the models pertaining to sales, forecasting and inventory control. Most of the inventory problems assume a given price structure and very less has been researched on the relationship between the two. Here, in this paper, inventory problem has been studied under the pricing structure for a Just-in-Time (JIT) system. The supplier offers the buyer a price discount, which the buyer finds beneficial to him and hence, orders more frequently. This allows both the buyer and the supplier to have less amount of inventory and thus, both minimize the cost. An analysis of how the supplier structures the terms and conditions of an optimal quantity schedule is discussed here.","PeriodicalId":154053,"journal":{"name":"2007 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125758041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-11-19DOI: 10.1109/SOLI.2007.4383944
Yao Wei-kun, Zhou Mei-hua, Meng Jian
Customer loyalty evolution experienced cognitive-affective-conative-action sequence. During the process of cognitive loyalty forming, utilitarian value is the primary factor of customer value, which drive the forming of cognitive loyalty via customer satisfaction; From cognitive loyalty to affective loyalty, hedonic value is the crucial impetus to drive the evolution via customer satisfaction and customer trust; From affective loyalty to conative loyalty, customer value perception is more nonfigurative and general, and drive the evolution via customer satisfaction and customer commitment; From conative loyalty to action loyalty, the evolution is driven by customer commitment and switching barrier which was determined by value perception.
{"title":"Value-based Customer Loyalty Evolution","authors":"Yao Wei-kun, Zhou Mei-hua, Meng Jian","doi":"10.1109/SOLI.2007.4383944","DOIUrl":"https://doi.org/10.1109/SOLI.2007.4383944","url":null,"abstract":"Customer loyalty evolution experienced cognitive-affective-conative-action sequence. During the process of cognitive loyalty forming, utilitarian value is the primary factor of customer value, which drive the forming of cognitive loyalty via customer satisfaction; From cognitive loyalty to affective loyalty, hedonic value is the crucial impetus to drive the evolution via customer satisfaction and customer trust; From affective loyalty to conative loyalty, customer value perception is more nonfigurative and general, and drive the evolution via customer satisfaction and customer commitment; From conative loyalty to action loyalty, the evolution is driven by customer commitment and switching barrier which was determined by value perception.","PeriodicalId":154053,"journal":{"name":"2007 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129261851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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