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OCR post-processing is an important step to improve OCR text accuracy. It includes two main tasks, error detection and error correction. Hill climbing algorithm is a heuristic search method used for solving optimization problems. In this paper, we present a novel OCR error correction approach using an adapted version of the Hill climbing algorithm. Correction candidates of OCR errors are explored by random character edits and evolved with the Hill climbing. The character edit patterns are obtained from the training data. The proposed model is evaluated on the benchmark dataset in the OCR post-correction competition of the International Conference on Document Analysis and Recognition 2017. It is shown that our model outperforms various baseline approaches in the competition. In addition, the randomness of the proposed algorithm is analyzed to verify its stability under parameter configurations. [ABSTRACT FROM AUTHOR]

This paper is a continuation of the paper [8] and presents more applications of Fitzpatrick functions for solving optimization problems. The main purpose of the present work is to introduce some new properties of Fitzpatrick functions useful for solving optimization problems, using also their already presented specific properties, as the maximal monotonicity, proper, convex and lower semi-continuity. [ABSTRACT FROM AUTHOR]

Portfolio methods provide the identification of the market position of a product offered by a particular enterprise, and thus indicate the organization's long-term development prospects. In this paper the authors present the possibility of applying portfolio methods for the classification of Unmanned Aerial Vehicles (UAV) used in military engineering. The computations included 15 UAV models available on the Polish market. The analysis made it possible to classify the UAVs in question into one of the four groups, and to choose the optimal UAV model with a view to one of the criteria adopted. [ABSTRACT FROM AUTHOR]

Recently, numerous studies have been concerned in conjugate gradient methods for solving large-scale unconstrained optimization method. In this paper, a three-term conjugate gradient method is proposed for unconstrained optimization which always satisfies sufficient descent direction and namely as Three-Term Rivaie-Mustafa-Ismail-Leong (TTRMIL). Under standard conditions, TTRMIL method is proved to be globally convergent under strong-Wolfe line search. Finally, numerical results are provided for the purpose of comparison. [ABSTRACT FROM AUTHOR]

The field of nature inspired computing and optimization techniques have evolved to solve difficult optimization problem in diverse fields of engineering, science and technology. The firefly attraction process is mimicked in the algorithm for solving optimizing proble3ms. In Firefly Algorithm (FA) sorting of fireflies is done by using sorting algorithm. The original FA is proposed with bubble sort for ranking the fireflies. In this paper, the quick sort replaces bubble sort to decrease the time complexity of FA. The dataset used is unconstrained benchmark functions from CEC 2005 [22]. The comparison of FA using bubble sort and FA using quick sort is performed with respect to best, worst, mean, standard deviation, number of comparisons and execution time. The experimental result shows that FA using quick sort requires less number of comparisons but requires more execution time. The increased number of fireflies helps to converge into optimal solution whereas by varying dimension for algorithm performed better at a lower dimension than higher dimension. [ABSTRACT FROM AUTHOR]

Conjugate gradient (CG) methods are one of the tools in optimization. Due to its low computational memory requirement, this method is used in solving several of nonlinear unconstrained optimization problems from designs, economics, physics and engineering. In this paper, a new modification of CG family coefficient (βk) is proposed and posses global convergence under exact line search direction. Numerical experimental results based on the number of iterations and central processing unit (CPU) time show that the new βk performs better than some other well known CG methods under some standard test functions. [ABSTRACT FROM AUTHOR]

The search of routes with multiple Quality of Service (QoS) constraints from sources to destinations connected by networks is a Non Polynomial (NP) problem, which can be approached using Genetic Algorithms (GAs). These are heuristic algorithms that simulate the natural evolution process to solve optimization problems. In this paper we elaborate on tree-based GAs which represent the set of paths from source to destination as a tree. While existing GA applications use m-ary or binary encoding representing single paths and classes of paths in chromosomes, respectively, we propose a GA application with hybrid encoding which uses both of them. This application uses binary encoding from the first iteration until good classes of paths are found and later encodes the best paths of these classes with m-ary encoding. Its objective is taking advantage of the fast convergence due to the per class-processing of binary chromosomes and the lower computational cost of the single path processing of m-ary chromosomes. Simulation results show the performance, in terms of convergence speed, of the proposed GA application with hybrid encoding. [ABSTRACT FROM AUTHOR]

Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered. [ABSTRACT FROM AUTHOR]

This paper proposes the impact assessment of the workers in the optimal time of operations in a Flexible Job Shop Scheduling Problem. In this work, a real enterprise was studied. The problem consists in finding the workers operations schedule, taking into account the precedence constraints. The main objective is to minimize the finish time of the last task completed in the schedule. The genetic algorithm was used to solve the optimization problem and some numerical results are presented. [ABSTRACT FROM AUTHOR]

Assembly sequence planning (ASP) plays an important role in manufacturing because it determines the investment on the assembly facilities. Recently, various research works have been done to optimize the ASP problem using different optimization algorithms. Besides the algorithm efficiency, another factor that directly contributed to the quality of the solution is how the problem is modelled. According to the existing research, the most accurate approach to represent the ASP is to model base on the part of product. However, this approach resulting in the large number of assembly sequence possibility, and finally make the optimization process become harder. This paper proposed a simpler version of part-based representation using the base part concept. In the proposed model, the base part for the product is defined prior to the establishment of the precedence constraint. This approach has contributed to a smaller search space that resulting in better chance to obtain optimum solution during the optimization. The proposed ASP modelling approach however limited the number of possible solution, since the base part was fixed prior to the optimization. [ABSTRACT FROM AUTHOR]

A new inverse reliability-based optimization method is presented. It is aimed for solving inverse reliability problems with multiple solutions of optimal design parameters with respect to the target reliability constraints. The method is based on coupling of aimed multilevel sampling optimization method and artificial neural network-based inverse reliability method. Emphasis was placed on the reduction in computational effort, which is further enhanced by using a small-sample simulation technique. A unique optimum solution is obtained by introducing an optimization with an objective function related to deterministic constraint while reliability constraints are implicitly considered via inverse reliability analysis. The validity and efficiency of the method is shown on testing example with three design parameters and one reliability constraint. Both cases with uncorrelated as well as correlated random variables have been tested. [ABSTRACT FROM AUTHOR]

Conjugate gradient (CG) method is an important technique in unconstrained optimization, due to its effectiveness and low memory requirements. The focus of this paper is to introduce a new CG method for solving large scale unconstrained optimization. Theoretical proofs show that the new method fulfills sufficient descent condition if strong Wolfe-Powell inexact line search is used. Besides, computational results show that our proposed method outperforms to other existing CG methods. [ABSTRACT FROM AUTHOR]

The researches of periodic structures have a long history with the main contents confined in the field of forward problem. In this paper, the inverse problem is considered and an overall frame is proposed which includes two main stages, i.e., the band gap criterion and its optimization. As a preliminary investigation, the inverse problem of the flexural vibrational band gap of a periodically supported beam is analyzed. According to existing knowledge of its forward problem, the band gap criterion is given in implicit form. Then, two cases with three independent parameters, namely the double supported case and the triple one, are studied in detail and the explicit expressions of the feasible domain are constructed by numerical fitting. Finally, the parameter optimization of the double supported case with three variables is conducted using genetic algorithm aiming for the best mean attenuation within specified frequency band. [ABSTRACT FROM AUTHOR]

The optimum allocations of multiple trackers for an infinite land will be either rectangular allocation parallel to N-S and E-W axis, or checkerboard allocation. We solved an optimization problem. Type of the optimum allocation pattern and its aspect ratio depend on latitude, climate pattern, aspect ratio of panels and space factor. Roughly speaking, the checkerboard allocation will be desired to higher latitude, sunshine in summer, higher space factor, and highly landscaped rectangular solar panels. A decision flow chart was proposed by the calculation result. [ABSTRACT FROM AUTHOR]

In the paper the problem of tool path optimization for CNC (Computer Numerical Control) cutting machines is considered. The classification of the cutting techniques is offered. We also propose a new classification of toll path problems. The tasks of cost minimization and time minimization for standard cutting technique (Continuous Cutting Problem, CCP) and for one of non-standard cutting techniques (Segment Continuous Cutting Problem, SCCP) are formalized. We show that the optimization tasks can be interpreted as discrete optimization problem (generalized travel salesman problem with additional constraints, GTSP). Formalization of some constraints for these tasks is described. For the solution GTSP we offer to use mathematical model of Prof. Chentsov based on concept of a megalopolis and dynamic programming. [ABSTRACT FROM AUTHOR]

The aim of this paper is to find an optimal individual diet that 1st. Gives all necessary ingredients with proper weighs and 2nd. Limits included unhealthy substances. Real data for some people are used and the problems are solved. [ABSTRACT FROM AUTHOR]

Examination timetabling is a well-studied combinatorial optimization problem involving scheduling a set of examinations into a restricted number of time-slots while satisfying a defined set of constraints. This paper presents a real-world, capacitated examination timetabling problem from Universiti Utara Malaysia (UUM), Malaysia. This dataset differs from the others reported in the literature with respect to its size, complexity and constraints. Until recently, examination timetabling in UUM is done manually with a little guidance from spreadsheet computer software for checking clashes. The propriety system is unable to do the examination timetabling automatically. Besides, the introduced datasets also consider a new constraint that has never been modeled before in timetabling literature, which is lecturer's preference. Moreover, splitting examination across several rooms and a number of hard constraints such as no mixed duration of examination within individual periods, clashes free schedule and room capacity requirement are also need to be adhered. These constraints provide an additional challenge in solving the examination timetabling problem, mainly at UUM. In this paper, graph coloring heuristics are employed to schedule examinations at each step during timetable construction. We used the concept of bin packing heuristics to assign examination to room with respect to the capacity. Since this is a new dataset and no solutions have been published in the literature yet, we only compare the results with an existing manual solution. It is found that the proposed constructive heuristic able to produce good quality solution for the tested problem. The proposed graph coloring heuristics are proved to be superior to the current method employed by the University and found to perform well in comparison. [ABSTRACT FROM AUTHOR]

The performed studies are aimed at the increase of the capacity of operating and prospective wheel shops by means of intensification of the use of existing equipment and creation of new specialized high-performance equipment for the repair and formation of wheelsets. To solve this problem, a technique is developed for the optimization of the parameters of equipment for wheel shops, including a mathematical model with a number of technical and technological limitations. The minimum value of the reduced costs is taken as the optimization criterion. As a result of the performed calculations, the optimal cutting conditions are obtained for the processing of carriage and locomotive axles from forgings and cross rolling products, taking into account the prospects for the development of cutting tools and the achievements of domestic and foreign machine tools. Based on the optimal ranges of changes in the rotation frequency of the principal movement and feed drive systems, and a number of other parameters of the tools, obtained as a result of calculations, the adjustments were made to the processing schemes and diagrammatic works of both existing and prospective machine tools of the enterprises wheel shops. A technical assignment is developed for the design and manufacture of a special multi-cutting semi-automatic lathe with two tool heads for axes. [ABSTRACT FROM AUTHOR]

We have reviewed the simulation modeling problems concerning the technological process of transport support. We have proposed the solutions to optimization problems. An optimal path algorithm has been developed in the Anylogic software. Also, the optimization process of the number of vehicles in the specified conditions has been performed. The results of computer experiments are given. [ABSTRACT FROM AUTHOR]

The existence of Hadamard matrices remains one of the most challenging open questions in combinatorics. Substantial progress on their existence has resulted from advances in algebraic design theory using deep connections with linear algebra, abstract algebra, finite geometry, number theory, combinatorics and optimization. The construction and analysis of Hadamard matrices, and their use on combinatorial designs, play an important role nowadays in diverse fields such as: quantum information, communications, networking, cryptography, biometry and security. Hadamard Matrices are present in our daily life and they give rise to a class of block designs named Hadamard configurations. Different applications of it based on new technologies and codes of figures such as QR Codes are present almost everywhere. Balanced Incomplete Block Designs (BIBD) are very well known as a tool to solve emerging problems in this area. Illustrations and applications to authentication codes and secret sharing schemes will be presented. [ABSTRACT FROM AUTHOR]