Solving a Class of Cut-Generating Linear Programs via Machine Learning

Cut-generating linear programs (CGLPs) play a key role as a separation oracle to produce valid inequalities for the feasible region of mixed-integer programs. When incorporated inside branch-and-bound, the cutting planes obtained from CGLPs help to tighten relaxations and improve dual bounds. However, running the CGLPs at the nodes of the branch-and-bound tree is computationally cumbersome due to the large number of node candidates and the lack of a priori knowledge on which nodes admit useful cutting planes. As a result, CGLPs are often avoided at default settings of branch-and-cut algorithms despite their potential impact on improving dual bounds. In this paper, we propose a novel framework based on machine learning to approximate the optimal value of a CGLP class that determines whether a cutting plane can be generated at a node of the branch-and-bound tree. Translating the CGLP as an indicator function of the objective function vector, we show that it can be approximated through conventional data classification techniques. We provide a systematic procedure to efficiently generate training data sets for the corresponding classification problem based on the CGLP structure. We conduct computational experiments on benchmark instances using classification methods such as logistic regression. These results suggest that the approximate CGLP obtained from classification can improve the solution time compared to that of conventional cutting plane methods. Our proposed framework can be efficiently applied to a large number of nodes in the branch-and-bound tree to identify the best candidates for adding a cut

Managerial ability and intellectual capital disclosure

PurposeWhile prior research in the area of intellectual capital (IC) disclosure has mainly focused on firm, board and audit committee characteristics, there is little research on whether managerial characteristics are associated with IC disclosure. This study aims to examine the relationship between managerial ability (MA) and the extent of IC disclosure.Design/methodology/approachThe study sample comprises 1,098 firm-year observations of Iranian listed firms during 2012–2017. This study uses the checklist developed by Li et al. (2008) and adopts a content analysis approach and calculates the IC disclosure index in 62 dimensions within three categories: human capital, structural capital and relational capital. To measure MA, this study uses the managerial ability score (MA-Score) developed by Demerjian et al. (2012) for Iranian firms.FindingsThe results show that MA is significantly and negatively associated with the overall extent of IC disclosure and all the three components of IC (human capital, structural capital and relational capital). Further analysis shows that the interaction between MA and firm performance is positive and significant, suggesting that the negative relationship between MA and IC disclosure is less pronounced for high-performing firms. This study addresses the potential endogeneity issue by using the propensity score matching approach. The findings are also robust to the alternative measure of MA.Originality/valueThis study contributes to both the MA literature and the IC disclosure literature. To the best of the authors' knowledge, this study is the first to provide empirical evidence on the relationship between MA and IC disclosure.</p

Does Securities Commission Oversight Reduce the Complexity of Financial Reporting?

We investigate whether securities commission oversight reduces the complexity of financial reporting (complexity). To measure the securities commission oversight, we use comment letters from securities commission of Iran. Further, to measure the complexity, we employ the Fog index. Using a difference-in-differences design with a propensity score matching approach, we find that the securities commission oversight reduces the complexity. Furthermore, we document that the impact of securities commission oversight on the complexity is stronger for firms with higher corporate governance quality. In addition, we document that the impact of securities commission oversight on the complexity (1) is not limited to one year and persists through at least two years later; and (2) is not higher for firms that receive more comment letters. We further document the spillover effect of securities commission oversight, in the sense that firms not receiving any comment letter reduce their complexity if the securities commission has commented on the industry leader or a close rival. Collectively, this paper, on the one hand, provides related evidence for the international debate on whether securities commissions could provide beneficial effects; and on the other hand, contributes to the literature on the complexity and its reducing factors that are among the most important issues in the context of international financial reporting.</p

Metal-salt enhanced grafting of vinylpyridine and vinylimidazole monomer combinations in radiation grafted membranes for high-temperature PEM fuel cells

Proton exchange membranes were prepared and characterized for utilization in high-temperature proton exchange membrane fuel cells, HT-PEMFCs. 1-vinylimidazole (1-VIm) and 4-vinylpyridine (4VP) monomers were simultaneously grafted onto pre-irradiated ETFE (ethylene-co-tetrafluoroethylene) films which were prepared using gamma-rays with a dose of 100 kGy, as a robust substrate to prepare acid-base composite membranes. The grafting reaction was performed at 60 degrees C for 24 h followed by protonation via phosphoric acid doping in the subsequent step. The effect of adding ferrous salts as promoters in grafting was investigated by characterization of resultant membranes via thermal gravimetric analysis and mechanical tests. The fuel cell tests were conducted under different relative humidities (RHs) and applied temperatures. Membranes prepared with salt addition exhibited superior proton conductivities. Results including up to 80 mS cm(-1) conductivity at 110 degrees C in 60% RH and excellent thermal stability, even at 300 degrees C, suggest these membranes are promising for HT-PEMFC applications

Consistency in integer programming

In this thesis, we study the role of cutting planes in reducing the size of the branch-and-bound tree for integer programs. Cutting planes are traditionally used to tighten relaxations of the problem by excluding fractional solutions, which leads to improving the dual bounds. In this research, we study a fundamentally different role of cutting planes that target excluding integer infeasible partial solutions, which leads to improving consistency of the set. Consistency helps to reduce backtracking, thereby reducing the size of the search tree. We investigate the connections between consistency and convex hull, and design a cutting plane framework to achieve consistency. One of the practical challenges in incorporating cutting planes inside of branch-and-bound is the running time required to solve a cut-generating problem. To address this difficulty, we design a function approximation framework to find an estimate for the cut-generating functions. We use machine learning methods that provide a classifier for the binary outcome of the indicator function representing the cut-generating oracle. Computational experiments conducted show significant time improvement as well as size reduction of B&B tree for the proposed approach compared to traditional technique

Consistency in integer programming

In this thesis, we study the role of cutting planes in reducing the size of the branch-and-bound tree for integer programs. Cutting planes are traditionally used to tighten relaxations of the problem by excluding fractional solutions, which leads to improving the dual bounds. In this research, we study a fundamentally different role of cutting planes that target excluding integer infeasible partial solutions, which leads to improving consistency of the set. Consistency helps to reduce backtracking, thereby reducing the size of the search tree. We investigate the connections between consistency and convex hull, and design a cutting plane framework to achieve consistency. One of the practical challenges in incorporating cutting planes inside of branch-and-bound is the running time required to solve a cut-generating problem. To address this difficulty, we design a function approximation framework to find an estimate for the cut-generating functions. We use machine learning methods that provide a classifier for the binary outcome of the indicator function representing the cut-generating oracle. Computational experiments conducted show significant time improvement as well as size reduction of B&B tree for the proposed approach compared to traditional technique

Consistency in integer programming

In this thesis, we study the role of cutting planes in reducing the size of the branch-and-bound tree for integer programs. Cutting planes are traditionally used to tighten relaxations of the problem by excluding fractional solutions, which leads to improving the dual bounds. In this research, we study a fundamentally different role of cutting planes that target excluding integer infeasible partial solutions, which leads to improving consistency of the set. Consistency helps to reduce backtracking, thereby reducing the size of the search tree. We investigate the connections between consistency and convex hull, and design a cutting plane framework to achieve consistency. One of the practical challenges in incorporating cutting planes inside of branch-and-bound is the running time required to solve a cut-generating problem. To address this difficulty, we design a function approximation framework to find an estimate for the cut-generating functions. We use machine learning methods that provide a classifier for the binary outcome of the indicator function representing the cut-generating oracle. Computational experiments conducted show significant time improvement as well as size reduction of B&B tree for the proposed approach compared to traditional technique

Consistency in integer programming

In this thesis, we study the role of cutting planes in reducing the size of the branch-and-bound tree for integer programs. Cutting planes are traditionally used to tighten relaxations of the problem by excluding fractional solutions, which leads to improving the dual bounds. In this research, we study a fundamentally different role of cutting planes that target excluding integer infeasible partial solutions, which leads to improving consistency of the set. Consistency helps to reduce backtracking, thereby reducing the size of the search tree. We investigate the connections between consistency and convex hull, and design a cutting plane framework to achieve consistency. One of the practical challenges in incorporating cutting planes inside of branch-and-bound is the running time required to solve a cut-generating problem. To address this difficulty, we design a function approximation framework to find an estimate for the cut-generating functions. We use machine learning methods that provide a classifier for the binary outcome of the indicator function representing the cut-generating oracle. Computational experiments conducted show significant time improvement as well as size reduction of B&B tree for the proposed approach compared to traditional technique

Electrospun sulfonated silica-based proton exchange membranes for pem fuel cells

Proton exchange membrane fuel cells (PEMFCs) are considered as the most promising alternative systems for fossil fuel-based devices due to their outstanding characteristics such as high efficiency and applicability in a wide range of sectors. Nevertheless, the materials characteristics and system designs with promising performance, durability, and cost-effectiveness still need to be improved for their commercialization. In this regard, a growing amount of research has been conducted to enhance the properties of their various parts, particularly the membrane as the heart of a PEMFC which serves numerous vital functions. Nafion® membranes are commonly used as the membrane material in PEMFCs due to their several advantages but they suffer mainly from insufficient proton conductivity at low relative humidity (RH) and elevated temperatures as well as high-cost production cost. To overcome the disadvantages of Nafion® membranes, in the present thesis two different strategies were used to synthesis and fabrication of proton conductive membranes with a promising performance at low humidity operation conditions. In the first approach, for substitution of Nafion® membranes sulfonated silica/ poly (vinylidene fluoride-co trifluoroethylene)-based (P(VDF-TrFE)) and sulfonated silica/ poly (vinylidene fluoride)-based (PVDF) hybrid membranes were prepared via single electrospinning method where sulfonated silica (S-SiO2) nanoparticles were used as proton conductive additives and PVDF or P(VDF-TrFE) as the carrier polymers. Hybrid S-SiO2/P(VDF-TrFE) membranes showed a superior proton conductivity (102 mS/cm) at 80°C and 100% RH than the S-SiO2/ PVDF membranes (43 mS/cm) at the same conditions. These iv superior results are due to the P(VDF-TrFE) polymer in the hybrid membrane structure that creates larger micro-channels for proton conduction. In the second approach, modification of Nafion® membranes were investigated by incorporation of sulfonated silica (S-SiO2) network into the Nafion®/PVDF or Nafion®/P(VDF-TrFE) fibrous mats. For this purpose, a single-step dual-electrospinning and sol-gel method were combined for the preparation of composite membranes as a fast and scalable technique. In this part of the thesis, the P(VDF-TrFE)-based membranes showed higher proton conductivity than PVDF-based ones (132 vs. 79 mS/cm at 80°C and 100% RH). Moreover, composite membranes exhibit superior cell performance especially at lower applied humidity conditions. The maximum power density is at 344 mW/cm2 60% RH, and this value is higher than the PVDF-based membranes which are 190 mW/cm2 at the same conditions. These observations suggest that P(VDF-TrFE)-based membranes can be considered as promising alternative membranes for PEMFC applications operating at low humidity conditions