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Homomorphic evaluation of hash functions offers a solution to the challenge of data integrity authentication in the context of homomorphic encryption. The earliest attempt to achieve homomorphic evaluation of SHA-256 hash function was proposed by Mella and Susella (in: Cryptography and coding—14th IMA international conference, IMACC 2013. Lecture notes in computer science, vol 8308. Springer, Heidelberg, pp 28–44, 2013. https://doi.org/10.1007/978-3-642-45239-0%5f3.) based on the BGV scheme. Unfortunately, their implementation faced significant limitations due to the exceedingly high multiplicative depth, rendering it impractical. Recently, a homomorphic implementation of SHA-256 based on the TFHE scheme (Homomorphic evaluation of SHA-256. https://github.com/zama-ai/tfhe-rs/tree/main/tfhe/examples/sha256%5fbool) brings it from theory to reality, however, its current efficiency remains insufficient. In this paper, we revisit the homomorphic evaluation of the SHA-256 hash function in the context of TFHE, further reducing the reliance on gate bootstrapping and enhancing evaluation latency. Specifically, we primarily utilize ternary gates to reduce the number of gate bootstrappings required for logic functions in message expansion and addition of modulo 2 32 in iterative compression. Furthermore, we demonstrate that our optimization techniques are applicable to the Chinese commercial cryptographic hash SM3. Finally, we give specific comparative implementations based on the TFHE-rs library. Experiments demonstrate that our optimization techniques lead to an improvement of approximately 35–50% compared with the state-of-the-art result under different cores. [ABSTRACT FROM AUTHOR]

Provides information on the inverse problem, design and optimization symposium to be held in Rio de Janeiro, Brazil from March 17 to 19, 2004. Motivation and objectives; Symposium topics; Symposium fees.

We are presenting in this special issue selected, peer-reviewed, papers that were presented at the 1st International Symposium and 10th Balkan Conference on Operational Research (BALCOR 2011), which was held during September 22-24, 2011, in Thessaloniki, Greece. [ABSTRACT FROM PUBLISHER]

A preface for the special issue of "Journal of Global Optimization" featuring papers selected from the 8th International Conference on Optimization: Techniques and Applications held in Shanghai, China is presented.

A conference-cum-workshop on Game Theory and Optimization was held at the Indian Institute of Technology Madras, during June 6–10, 2016. One of the primary objectives of the event was to commemorate the 75th birthday of Professor T. Parthasarathy, fondly referred to as TP. A special session was devoted to his life and mathematical career. This provided a platform for many of TP's students and collaborators to share their experiences with the audience. The conference was made possible through funding from the National Mathematics Initiative. Additional funding was received from the Office of Alumni and International Relations, the Departments of Mathematics, and Management Studies, Indian Institute of Technology Madras (IIT Madras). Following is a brief overview of the contributions to this special issue, a biography of Professor TP, and a list of his publications. The Guest Editors would like to thank all the authors, Annals of Operations Research Editor-in-Chief, Endre Boros, and all referees who provided peer review. This special issue would not have been possible without their valuable time and input. [ABSTRACT FROM AUTHOR]

The ninth annual IEEE International Conference on Automation Science and Engineering (IEEE CASE), sponsored by the IEEE Robotics and Automation Society (RAS), was successfully held 17-21 August 2013 in Madison, Wisconsin, USA. Under the theme of "Automation in Practice," topics in the conference touched a wide spectrum of automation: fundamental theory, scheduling and optimization, manufacturing and supply chain, informatics, and emerging topics such as: civil and building automation, health-care automation, energy systems, and networked systems. In the current year, we had over 300 attendees and a record number of 322 submissions from 29 countries. In addition to regular paper submissions, we solicited presentationonly submissions to permit authors to present particularly new developmental or application work. The final program included 193 papers and 28 presentation-only contributions. (Table 1 indicates the awards presented at the conference.) We would like to sincerely thank the contributions of all the participants as the general chair and program chair of the IEEE CASE 2013. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a unified framework for opportunistic fair scheduling in wireless systems. We consider a TDMA type of multiple access scheme, in which only one user can be scheduled in each time-slot. For opportunistic fair scheduling in such a system, some nice frameworks have been developed in the previous works, such as Agrawal and Subramanian (Allerton conference on communication, control and computing, 2002), Liu et al. (IEEE Journal of Selected Areas in Communications 19(10): 2053–2065, 2001) and Liu et al. (Computer Networks 41(4): 451–474, 2003). However, in this paper, we consider a more general problem that can accommodate more general types of fairness, and more general types of utility functions than those in the previous works. In addition to those generalizations, we develop a new framework for opportunistic fair scheduling based on the duality theory, which is different from those in the previous works. The duality theory is a well-defined theory in the mathematical optimization area. Hence, it can provide a unified framework for many different types of problems. In fact, we show that two different frameworks in Agrawal and Subramanian (Allerton conference on communication, control and computing, 2002), Liu et al. (IEEE Journal of Selected Areas in Communications 19(10): 2053–2065, 2001) and Liu et al. (Computer Networks 41(4): 451–474, 2003) are special cases of ours. In addition, by using the unified framework developed in this paper, we can not only develop various opportunistic fair scheduling schemes but also analyze the developed algorithm more rigorously and systematically. [ABSTRACT FROM AUTHOR]

Information about several papers discussed at the International Symposium on Physical Design is presented. It features new methods for extraction of spatial correlation and discusses placement-related problems such as optimization of wire lengths, 3-dimensional floorplanning, and the impact of clustering methods on placement algorithms. Classic topics including routing, decoupling capacitor optimization, and buffer insertion were also included.

Information about several papers discusses in 11th International Conference on Stochastic Programming which was held in Vienna, Austria on August 27, 2007 is presented. The conference was aimed at closing the gap between the field of stochastic programming and the area of robust optimization and optimization under uncertainty. The conference featured Arkadi Nemirovski, Darinka Dentcheva and Andrzej Ruszczynski.

Research highlights: Through a broad review of literature and practices, this paper has helped confirm Forest Engineering as a unique discipline by providing definition, highlighting achievements of the last decade and suggesting future directions. Background and Objectives: Forest Engineering is a study program offered by many universities worldwide. It is also the main subject of three international scientific journals, three important scientific conferences and a division of the International Union of Forestry Research Organizations. That points at a strong interest, a general common understanding and a strong local diversification. The paper aims to suggest generally valid definitions, while offering a description of the main achievements and a hypothesis about future directions. Results: The review identified examples that include higher-level mechanization, commencement of automation and system optimization, and specifically the emerging field of biomass and bioenergy integration as examples of major forest engineering achievements of the last decade. Higher levels of automation including autonomous machine operation, and integration of intelligent and linked technology are examples of future directions. Conclusions: As with other disciplines, most Forest Engineering teaching, research or applications are multi-disciplinary. However, the review has highlighted specific achievements and future directions that helps define Forest Engineering as a unique discipline and one that can make a major contribution to the broader field of forest management practices. [ABSTRACT FROM AUTHOR]

The article focuses on the papers on food scarce events and agricultural market consequences that were presented in a principal paper session at the 2008 Agricultural and Applied Economics Association (AAEA) annual meeting in Orlando, Florida. It states that Nganje and Bier's paper investigate the value of risk reductions by employing game theory and stochastic optimization, hypothesizing that enhanced protection is obtained under coordination. The paper of Stinson, Ghosh, Kinsey and Degeneffe, however, aims to add to the empirical information on public perceptions regarding food defense and safety programs based on surveys executed both before and after national recalls.

An introduction is presented which discusses various papers presented during the International Symposium on Mathematical Programming (ISMP) in Pittsburgh, Pennsylvania from July 12-17, 2015 including coordinate descent algorithms, copositive optimization and mathematical optimization.

In recent years, the research in the field of optimization has been very active in the Asia-Pacific region, particularly in China and Japan. To promote research activities further and bring significant impact on the development of research, the Second Japanese-Sino Optimization Meeting (JSOM2002) was held in Kyoto, Japan, on September 25-27, 2002. About 130 participants not only from Asia but also from North America and Europe attended the meeting and exchanged their ideas on the latest work in optimization and related areas. In response to our call-for-papers to a special issue for the meeting, a significant number of manuscripts were submitted for possible publication. After careful review, 17 papers have finally been accepted. Reflecting the wide scope of the meeting, these papers cover extremely diverse topics of theory and applications of methods in continuous optimization, discrete optimization, dynamic optimization, and stochastic optimization. They are published in this and the next issues of Optimization Methods & Software. We are thankful to all authors who submitted their papers to the special issue and all anonymous referees who kindly helped us by reviewing the manuscripts carefully. Last but not least, we are grateful to Oleg Burdakov for his constant and generous support. [ABSTRACT FROM AUTHOR]

The application of quantum-behaved particle swarm optimization to multiobjective problems has attracted more and more attention recently. However, in order to extend quantum-behaved particle swarm optimization to multiobjective context, two major problems, namely the selection of personal and global best positions and the maintenance of population diversity, need to be taken into consideration. In this paper, a novel Cultural MOQPSO algorithm is proposed, in which cultural evolution mechanism is introduced into quantum-behaved particle swarm optimization to deal with multiobjective problems. In Cultural MOQPSO, the exemplar positions of each particle are obtained according to “belief space,” which contains different types of knowledge. Moreover, to increase population diversity and obtain continuous and even-distributed Pareto fronts, a combination-based update operator is proposed to update the external population in this paper. A comprehensive comparison of Cultural MOQPSO with some state-of-the-art evolutionary algorithms on several benchmark test functions, including ZDT, DTLZ and CEC2009 test instances, demonstrates the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Abstract: Teaching–Learning-Based Optimization (TLBO) is recently being used as a new, reliable, accurate and robust optimization technique for global optimization over continuous spaces. Few variants of TLBO have been proposed by researchers to improve the performance of the basic TLBO algorithm. In this paper the authors investigate the performance of a new variant of TLBO called modified TLBO (mTLBO) for global function optimization problems. The performance of mTLBO is compared with the state-of-the art forms of Particle Swarm Optimization (PSO), Differential Evolution (DE) and Artificial Bee Colony (ABC) algorithms. Several advanced variants of PSO, DE and ABC are considered for the comparison purpose. The suite of benchmark functions are chosen from the competition and special session on real parameter optimization under IEEE Congress on Evolutionary Computation (CEC) 2005. Statistical hypothesis testing is undertaken to demonstrate the significance of mTLBO over other investigated algorithms. Finally, the paper investigates the data clustering performance of mTLBO over other evolutionary algorithms on a few standard synthetic and artificial datasets. Results of our work reveal that mTLBO performs better than many other algorithms investigated in this work. [Copyright &y& Elsevier]

Since it was firstly introduced by Torra and Narukawa ( The 18th IEEE International Conference on Fuzzy Systems, Jeju Island, Korea, , pp. 1378-1382), the hesitant fuzzy set has attracted more and more attention due to its powerfulness and efficiency in representing uncertainty and vagueness. This paper extends the classical VIKOR (vlsekriterijumska optimizacija i kompromisno resenje in serbian) method to accommodate hesitant fuzzy circumstances. Motivated by the hesitant normalized Manhattan distance, we develop the hesitant normalized Manhattan $$L_p$$-metric, the hesitant fuzzy group utility measure, the hesitant fuzzy individual regret measure, and the hesitant fuzzy compromise measure. Based on these new measures, we propose a hesitant fuzzy VIKOR method, and a practical example is provided to show that our method is very effective in solving multi-criteria decision making problems with hesitant preference information. [ABSTRACT FROM AUTHOR]

In this paper, a simple heuristic is suggested that allows quick scheduling of small-to-medium-sized conferences by the programme chair/organizer. Owing to the nature of the problem that the heuristic was designed to solve, no annealing or combinatorial optimization techniques were required. Additionally, there is no explicit objective function associated with the problem only some simple constraints. The suggested heuristic aims to allocate all the conference papers to sessions over the conference duration taking into account presenter-based preferences (PBP) and some implicit attendee- based preferences. The conference programme chair (PC) may also insert preferences as to the positioning of papers and sessions. The heuristic also permits the PC to allocate appropriate rooms to sessions based on expectations regarding attendance. Owing to the simple nature of the heuristic, all that is required to facilitate its operation is a small programme created using a standard database package. The suggested heuristic, which effectively is a set of rules to be affected in a specific sequence, has been successfully used to schedule a Western Decision Sciences Institute (WDSI) annual conference. The conference spanned four days, had over three hundred participants, involved over 80 sessions with 200 papers and 50 special sessions. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various articles related to optimization and optimal control with applications which were discussed in the 9th International Conference on Optimization: Techniques and Applications that was held in Taipei, Taiwan from December 12â€16, 2013.

The article introduces the current issue, which contains selected papers from the "Scientific Meeting 'Numerical Methods for Local and Global Optimization: Sequential and Parallel Algorithms,' including one about a local optima smoothing approach for solving global optimization problems, and another suggesting a method for constructing test functions for global optimization.

We investigate the theoretical complexity of branch-and-bound (BB) and cutting plane (CP) algorithms for mixed-integer optimization. In particular, we study the relative efficiency of BB and CP, when both are based on the same family of disjunctions. We extend a result of Dash (International Conference on Integer Programming and Combinatorial Optimization (IPCO), pp. 145–160, 2002) to the nonlinear setting which shows that for convex 0/1 problems, CP does at least as well as BB, with variable disjunctions. We sharpen this by giving instances of the stable set problem where we can provably establish that CP does exponentially better than BB. We further show that if one moves away from 0/1 sets, this advantage of CP over BB disappears; there are examples where BB finishes in O(1) time, but CP takes infinitely long to prove optimality, and exponentially long to get to arbitrarily close to the optimal value (for variable disjunctions). We next show that if the dimension is considered a fixed constant, then the situation reverses and BB does at least as well as CP (up to a polynomial blow up factor), for quite general families of disjunctions. This is also complemented by examples where this gap is exponential (in the size of the input data). [ABSTRACT FROM AUTHOR]

The article reports on the XXII All-Russian Conference on mathematical programming and applications, which was held in Ekaterinburg, Russia on February 24-28, 2003. It was organized by Institute of Mathematics and Mechanics of the Ural Branch of the Russian Academy of Sciences. The Organizing Committee of the Conference was chaired by Academician I.I. Eremin. The main topics discussed at the conference were as follows: (1) theory and methods of mathematical programming; (2) discrete optimization; (3) optimization and approximation.

In 2003, as part of a lecture series sponsored by the American Gaming Association, Richard LaBrie and Howard Shaffer issued a 'concept statement' titled Toward a Science of Gambling Regulation. They stated, "The set of gambling regulations within a jurisdiction represent that jurisdiction's strategy for preventing negative consequences....We propose that gambling regulations would be more effective if the regulatory process was science-based" (2003, p. 1). This paper represents a step towards scientifically analyzing variations in existing policies to determine how effective they are in reaching policy goals. A quasi-experimental matching procedure is utilized to assess the impacts of casinos at the county level. Additional analysis examines the effects of various policies on economic development outcomes. The findings suggest that more restrictive casino policies reduce the economic impacts associated with casino development. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented, which contains articles obtained from the Black Box Optimization Benchmarking (BBOB) workshops and the Genetic and Evolutionary Computation Conference (GECCO) that took place in 2009, 2010 and 2012.

Abstract: The optimization of tensor expressions with hundreds of terms is required for the development of accurate quantum chemistry models such as the coupled cluster method. In this paper, we address the effective exploitation of symmetry properties of tensors in performing algebraic transformations for minimizing operation count of tensor expressions. We develop rules to detect symmetries in intermediate tensors, cost models for tensor contractions with symmetries, and a canonical representation to facilitate effective common subexpression elimination. We demonstrate significant improvements to the operation counts for the coupled cluster method when compared to several state-of-the-art im-plementations. Furthermore, we show that tensor expressions optimized for a few input parameter combinations can be used to achieve operation counts within 3% of the optimal, for the entire parameter space of interest. [Copyright &y& Elsevier]

The article presents information on the 10th International Conference on Operations Research held March 6-9, 2012 in Havana, Cuba. Lectures delivered at the conference are noted. Lists are presented of lectures, discussions and research papers presented at the conference on topics including operations research, statistics and mathematical optimization.

Abstract: In this paper we study optimization problems with verifiable one-parameter selfish agents introduced by Auletta et al. [V. Auletta, R. De Prisco, P. Penna, P. Persiano, The power of verification for one-parameter agents, in: Proceedings of the 31st International Colloquium on Automata, Languages and Programming, ICALP, in: LNCS, vol. 3142, 2004, pp. 171–182]. Our goal is to allocate load among the agents, provided that the secret data of each agent is a single positive real number: the cost they incur per unit load. In such a setting the payment is given after the load completion, therefore if a positive load is assigned to an agent, we are able to verify if the agent declared to be faster than she actually is. We design truthful mechanisms when the agents’ type sets are upper-bounded by a finite value. We provide a truthful mechanism that is -approximate if the underlying algorithm is -approximate and weakly-monotone. Moreover, if type sets are also discrete, we provide a truthful mechanism preserving the approximation ratio of its algorithmic part. Our results improve the existing ones which provide truthful mechanisms dealing only with finite type sets and do not preserve the approximation ratio of the underlying algorithm. Finally, we give applications for our payment schemes. Firstly, we give a full characterization of the problem by using our techniques. Even if our payment schemes need upper-bounded type sets, every instance of can be “mapped” into an instance with upper-bounded type sets preserving the approximation ratio. In conclusion, we turn our attention to binary demand games. In particular, we show that the Minimum Radius Spanning Tree admits an exact truthful mechanism with verification achieving time (and space) complexity of the fastest centralized algorithm for it. This contrasts with a recent truthful mechanism for the same problem [G. Proietti, P. Widmayer, A truthful mechanism for the non-utilitarian minimum radius spanning tree problem, in: Proceedings of the 17th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA, ACM Press, 2005, pp. 195–202] which pays a linear factor with respect to the complexity of the fastest centralized algorithm. Such a result is extended to several binary demand games studied in literature. [Copyright &y& Elsevier]

Reports on the First International Conference on Optimization Methods and Software held on December 15-18, 2002, in Hangzhou, China. Purpose of the conference; Participants; Topics of the conference.

Explains that this special issue of "Numerical Linear Algebra with Applications" is devoted to the 2002 International Conference on "Preconditioning Methods for Optimal Control and Constrained Optimization Problems" held on October 23-25, 2002 in Netherlands. Goal of addressing complex issues related to preconditioning methods for constrained optimization and optimal control.

Owing to a technical problem in the submission process, selected presentations from the 7th International Conference on Boundary Elements, which took place in Paris, France, in September 2006 (http://beteq.engineeringconferences.net/), will not be published in a separate special issue. Links to these papers as they were published in the journal are listed at the end of this editorial. Copyright © 2008 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The article discusses the highlights of the 5th Cologne-Twente Workshop on Graphs and Combinatorial Optimization (CTW 2006) held in Lambrecht, Germany on June 5-9, 2006. Partners involved in the annual CTW event include the Politechnico di Milano, the University of Duisberg-Essen and the Universit&aagrave; degli Studi di Milano. Some of the topics discussed at the workshop were graph theory, discrete algorithms, and combinatorial optimization. It also addressed the Hamiltonian circuit problem.