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Order allocation in a multiple-vendor and quantity discount environment: A multi-objective decision making approach

Hengameh Hadian, Abdolhamid Eshraghniaye Jahromi, Mahnoosh Soleimani
2018 Management Science Letters  
Under such circumstances, most studies often formulate the problem as a Multi-Objective Linear Programming problem (MOLP), and then transform it to a Mixed Integer Programming problem (MIP) to handle the  ...  The large number of criteria and attributes are employed in this problem and they are employed in a comprehensive model to solve the multi-objective problem and to find the most preferred non dominated  ...  Burke et al. (2008) showed that purchasing problems under quantity discount policies are NP-hard and heuristics are valuable to find nearoptimal solutions for these problems.  ... 
doi:10.5267/j.msl.2018.7.003 fatcat:tdf7sommmbh7pp6gr2rzkfsnp4

ESPN: Efficient server placement in probabilistic networks with budget constraint

Dejun Yang, Xi Fang, Guoliang Xue
2011 2011 Proceedings IEEE INFOCOM  
We study this problem in both the single-hop model and the multi-hop model. We discuss the computational complexity of this problem and show that it is NP-hard under both models.  ...  If the costs of candidate locations are uniform, when extra budget is available in the future, the progressive feature of our algorithms allows for placing additional servers instead of relocating all  ...  As we will show later, even with uniform cost, it is NP-hard to determine the optimal server placement under both models. IV.  ... 
doi:10.1109/infcom.2011.5934908 dblp:conf/infocom/YangFX11 fatcat:bt3irys26zd3hpc34ukmflsc2q

Multi-Robot Task Allocation – Complexity and Approximation [article]

Haris Aziz, Hau Chan, Ágnes Cseh, Bo Li, Fahimeh Ramezani, Chenhao Wang
2021 arXiv   pre-print
Multi-robot task allocation is one of the most fundamental classes of problems in robotics and is crucial for various real-world robotic applications such as search, rescue and area exploration.  ...  Our aim is to consider a natural computational problem of allocating robots to complete the maximum number of tasks subject to budget constraints.  ...  ACKNOWLEDGEMENTS Aziz and Ramezani are supported by the Australian Defence Science and Technology Group (DSTG) under the project "Auctioning for distributed multi vehicle planning" (MYIP 9953) and by US  ... 
arXiv:2103.12370v1 fatcat:hyjxegwjbzcarpy4sgrbqunalm

Pareto Rank Learning in Multi-objective Evolutionary Algorithms

Chun-Wei Seah, Yew-Soon Ong, Ivor W. Tsang, Siwei Jiang
2012 2012 IEEE Congress on Evolutionary Computation  
obtain the Pareto-optimal solution set under a limited resource budget.  ...  In the context of multi-objective evolutionary optimizations, the challenge amplifies, since multiple criteria assessments, each defined by an "expensive" objective is necessary and it is desirable to  ...  optimal solution under limited computational budget.  ... 
doi:10.1109/cec.2012.6252865 dblp:conf/cec/SeahOTJ12 fatcat:r7lcxc3zazbopgmq2u53uxexdu

Solving multi-objective optimization problems in conservation with the reference point method

Yann Dujardin, Iadine Chadès, Majid Soleimani-damaneh
2018 PLoS ONE  
Reference point approaches solve multi-objective optimization problems by interactively representing the preferences of the decision-maker with a point in the criteria (objectives) space, called the reference  ...  We modelled and solved the following two problems in conservation: a dynamic multi-species management problem under uncertainty and a spatial allocation resource management problem.  ...  We considered a map of 3600 cells, where a decision consists in selecting a subset of 120 cells for management under a budget constraint.  ... 
doi:10.1371/journal.pone.0190748 pmid:29293650 pmcid:PMC5749871 fatcat:yavdmkyrgjd7jcg5cr2bjhnesa

Stochastic Budget Optimization in Internet Advertising

Bhaskar DasGupta, S. Muthukrishnan
2012 Algorithmica  
Our research answers some open problems raised by the authors in (Stochastic Models for Budget Optimization in Search-Based Advertising, Algorithmica, 58 (4), 1022-1044, 2010).  ...  Then, the best response can be abstracted as stochastic budget optimization problems to figure out how to spread a given budget across these keywords to maximize the expected number of clicks.  ...  Acknowledgements We thank the reviewers for their detailed comments which improved both the readability and the technical content of the paper.  ... 
doi:10.1007/s00453-012-9614-x fatcat:ox4xpqkb2vblpnbxyh6jyr7nui

Optimization of Media Mix Planning in Health Care System by an AHP Based Goal Programming Model

A. V. S. Prasad, Dr. Y. Raghunatha Reddy
2017 International Journal of Trend in Scientific Research and Development  
The problem was solved and results are discussed.  ...  In this paper, we present an analytic hierarchy process based goal programming model for media mix planning in health care system.  ...  The AHP was introduced by Saaty [21] which is a practical method to solve multi-criteria decision problems. AHP considers the data about a decision in multi-level hierarchy manner.  ... 
doi:10.31142/ijtsrd2210 fatcat:wlwtfc7ip5bujdewa6mtan2vme

Multi-Touch Attribution Based Budget Allocation in Online Advertising

Sahin Cem Geyik, Abhishek Saxena, Ali Dasdan
2014 Proceedings of 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining - ADKDD'14  
Budget allocation in online advertising deals with distributing the campaign (insertion order) level budgets to different sub-campaigns which employ different targeting criteria and may perform differently  ...  For this purpose, we employ both last-touch (last ad gets all credit) and multi-touch (many ads share the credit) attribution methodologies.  ...  The authors model budget optimization task as a constrained optimal control problem for a Markov Decision Process (MDP).  ... 
doi:10.1145/2648584.2648586 dblp:conf/kdd/GeyikSD14 fatcat:weialajuu5d7ll3ivomc4pam2a

Multi-Touch Attribution Based Budget Allocation in Online Advertising [article]

Sahin Cem Geyik, Abhishek Saxena, Ali Dasdan
2015 arXiv   pre-print
Budget allocation in online advertising deals with distributing the campaign (insertion order) level budgets to different sub-campaigns which employ different targeting criteria and may perform differently  ...  For this purpose, we employ both last-touch (last ad gets all credit) and multi-touch (many ads share the credit) attribution methodologies.  ...  The authors model budget optimization task as a constrained optimal control problem for a Markov Decision Process (MDP).  ... 
arXiv:1502.06657v1 fatcat:n2psw5cf5rfr7l4rtl6mp6wx5i

Solving multi-objective optimization problems in conservation with the reference point method [article]

Yann Dujardin, Iadine Chades
2016 arXiv   pre-print
Reference point approaches solve multi-objective optimization problems by interactively representing the preferences of the decision-maker with a point in the criteria space, called the reference point  ...  Our paper reviews some of the existing approaches to solve multi-objective decision problems and presents new multi-objective linear programming formulations of two multi-objective optimization problems  ...  of discrete optimization, is in general a hard task and requires a strong knowledge of the conservation problems and LP techniques.  ... 
arXiv:1611.07640v1 fatcat:nnqxydqtzvhubd45sdzktedkaq

On Load Shedding in Complex Event Processing [article]

Yeye He, Siddharth Barman, Jeffrey F. Naughton
2013 arXiv   pre-print
We formalize broad classes of CEP load-shedding scenarios as different optimization problems.  ...  We demonstrate an array of complexity results that reveal the hardness of these problems and construct shedding algorithms with performance guarantees.  ...  We show the hardness of this problem by a reduction from the Clique problem.  ... 
arXiv:1312.4283v1 fatcat:dedtrlmfabhudnirxtgbql2yf4

An extensive numerical benchmark study of deterministic vs. stochastic derivative-free global optimization algorithms [article]

Linas Stripinis, Remigijus Paulavičius
2022 arXiv   pre-print
Research in derivative-free global optimization is under active development, and many solution techniques are available today.  ...  This paper considers the solution to the bound-constrained, possibly black-box global optimization problem.  ...  The study was carried out using only a limited budget of objective function evaluations, typical for expensive global optimization problems.  ... 
arXiv:2209.05759v1 fatcat:4jyt5mg2mfaxdasrlfwepk6tsq

Model-Based Multi-objective Optimization: Taxonomy, Multi-Point Proposal, Toolbox and Benchmark [chapter]

Daniel Horn, Tobias Wagner, Dirk Biermann, Claus Weihs, Bernd Bischl
2015 Lecture Notes in Computer Science  
Within the last 10 years, many model-based multi-objective optimization algorithms have been proposed. In this paper, a taxonomy of these algorithms is derived.  ...  In particular for the classic ParEGO algorithm, significant improvements are obtained.  ...  budget MOEA using Surrogates [19] Other DOE (Sobol) Models for each objective Multi-objective optimization of model prediction Multi point, space-filling selection Total budget  ... 
doi:10.1007/978-3-319-15934-8_5 fatcat:tspwa3upefbn3edqn5mjprc5h4

An Electronic Market Model with Mathematical Formulation and Heuristics for Large-Scale Book Trading

Ali Haydar Özer
2017 Proceedings of the 2017 Federated Conference on Computer Science and Information Systems  
budget limit.  ...  The model allows participants to declare a budget limit so that for each participant, the difference between the cost of purchased books and the revenue obtained from sold books stays within the declared  ...  Among the generated 1600 problem instances, the MIP solver found the optimal solutions for 972 instances.  ... 
doi:10.15439/2017f291 dblp:conf/fedcsis/Ozer17 fatcat:bx5zfm7wirhrdl2dcdm5gy4wni

Portfolio Optimization for Defence Applications

Kyle Robert Harrison, Saber Elsayed, Ivan Garanovich, Terence Weir, Michael Galister, Sharon Boswell, Richard Taylor, Ruhul Sarker
2020 IEEE Access  
However, the literature regarding portfolio optimization for defense applications is rather sparse.  ...  The problem of designing an effective future defense force is quite complex and challenging.  ...  [59] considered a countermeasure prioritization problem such that the objective was to optimize the development of countermeasures under limited resources.  ... 
doi:10.1109/access.2020.2983141 fatcat:yxvillvsmjemrp4ooomfqrhaiq
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