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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Management Science and Financial Engineering
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Journal DOI :
The Korean Operations and Management Science Society
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Volume & Issues
Volume 18, Issue 2 - Nov 2012
Volume 18, Issue 1 - May 2012
Selecting the target year
Stock Returns and Market Making with Inventory
Park, Seyoung ; Jang, Bong-Gyu ;
Management Science and Financial Engineering, volume 18, issue 2, 2012, Pages 1~4
DOI : 10.7737/MSFE.2012.18.2.001
We study optimal trading strategy of a market maker with stock inventory. Following Avellaneda and Stoikov (2008), we assume the stock price follows a normal distribution. However, we take a constant expected rate of the stock return and assume that the stock volatility is an inverse function of the stock price level. We show that the optimal bid-ask spread of the market maker is wider for a higher expected rate of stock returns.
Stochastic Scheduling Problems for Maximizing the Expected Number of Early Jobs with Common or Exchangeable Due Dates
Choi, Jae Young ; Kim, Heung-Kyu ;
Management Science and Financial Engineering, volume 18, issue 2, 2012, Pages 5~11
DOI : 10.7737/MSFE.2012.18.2.005
In this paper, stochastic scheduling problems are considered when processing times and due dates follow arbitrary distributions and due dates are either common or exchangeable. For maximizing the expected number of early jobs, two policies, one, based on pairwise comparisons of the processing times, and the other, based on survivabilities, are introduced. In addition, it is shown that the former guarantees optimal solutions when the processing times and due dates are deterministic and that the latter guarantees optimal solutions when the due dates follow exponential distributions. Then a new approach, exploiting the two policies, is proposed and analyzed which turns out to give better job sequences in many situations. In fact, the new approach guarantees optimal solutions both when the processing times and due dates are deterministic and when the due dates follow exponential distributions.
General Set Covering for Feature Selection in Data Mining
Ma, Zhengyu ; Ryoo, Hong Seo ;
Management Science and Financial Engineering, volume 18, issue 2, 2012, Pages 13~17
DOI : 10.7737/MSFE.2012.18.2.013
Set covering has widely been accepted as a staple tool for feature selection in data mining. We present a generalized version of this classical combinatorial optimization model to make it better suited for the purpose and propose a surrogate relaxation-based procedure for its meta-heuristic solution. Mathematically and also numerically with experiments on 25 set covering instances, we demonstrate the utility of the proposed model and the proposed solution method.
Inverse Bin-packing Number Problems: NP-Hardness and Approximation Algorithms
Chung, Yerim ;
Management Science and Financial Engineering, volume 18, issue 2, 2012, Pages 19~22
DOI : 10.7737/MSFE.2012.18.2.019
In the bin-packing problem, we deal with how to pack the items by using a minimum number of bins. In the inverse bin-packing number problem, IBPN for short, we are given a list of items and a fixed number of bins. The objective is to perturb at the minimum cost the item-size vector so that all items can be packed into the prescribed number of bins. We show that IBPN is NP-hard and provide an approximation algorithm. We also consider a variant of IBPN where the prescribed solution value should be returned by a pre-selected specific approximation algorithm.
A Robust Joint Optimal Pricing and Lot-Sizing Model
Lim, Sungmook ;
Management Science and Financial Engineering, volume 18, issue 2, 2012, Pages 23~27
DOI : 10.7737/MSFE.2012.18.2.023
The problem of jointly determining a robust optimal bundle of price and order quantity for a retailer in a single-retailer, single supplier, single-product supply chain is considered. Demand is modeled as a decreasing power function of product price, and unit purchasing cost is modeled as a decreasing power function of order quantity and demand. Parameters defining the two power functions are uncertain but their possible values are characterized by ellipsoids. We extend a previous study in two ways; the purchasing cost function is generalized to take into account the economies of scale realized by higher product demand in addition to larger order quantity, and an exact transformation into an equivalent convex optimization program is developed instead of a geometric programming approximation scheme proposed in the previous study.