Sequence Of Operations Research Articles

ТЕХНОЛОГІЯ ОЦІНЮВАННЯ РЕЗУЛЬТАТИВНОСТІ БЕЗПЕКОВОЇ ДІЯЛЬНОСТІ ТОРГОВЕЛЬНОГО ПІДПРИЄМСТВА

COVID-19 and military operations have significantly changed the security situation for Ukrainian enterprises. The existing security systems were not ready for the existing critically high and difficult to predict dynamics of influence of previously secondary factors. The weak link turned out to be subsystems of information and analytical support, which were mostly focused on assessing the economic security of the enterprise based on reporting data. The current attempts of trade enterprises to adapt to the conditions of operation during the martial law actualized the problem of improving the information base of security activities. The purpose of the study is to develop a technology for evaluating the effectiveness of security activities of a trading enterprise. To develop a technology for evaluating the effectiveness of the security activities of a trading company, the following methods were used: induction and deduction, comparison and systematization – during the study of the existing practice of evaluating the security activities of enterprises; synthesis and analysis – for the calculation of primary indices, group and integral indicators; morphological analysis – to determine the list of primary indexes; expert survey – to establish weighting factors; graphic – for visual representation of theoretical and methodical material; abstract-logical – for theoretical generalizations and research conclusions. On the basis of a careful study of existing developments, a variant of the technology for evaluating the effectiveness of security activities of trade enterprises is proposed. The developed technology is a combination of knowledge (including methods, tools, techniques, principles), experience, organizational, technical and other decisions about the conditions, principles and sequence of operations, the implementation of which allows you to get a holistic vision of the course of security processes and the activity of sub security entities in the performance of specified tasks. The three components involve the calculation of a wide list of primary indicators, followed by their unification into group indicators and the determination of an integral indicator, which is facilitated by weighting factors that maximally take into account the specifics of trade and ensuring security in the conditions of the relevant economic entity. The use of the developed technology made it possible to obtain information about the actual results of the security activities of individual trade enterprises during 2021–2023, in particular in terms of countermeasures and elimination of threats related to COVID-19 and military actions.

ДІАГНОСТИКА ЕКОНОМІЧНОГО ЗРОСТАННЯ КОМПАНІЇ В УМОВАХ СТАЛОГО РОЗВИТКУ: ЕКОНОМІКО-МАТЕМАТИЧНІ ОСНОВИ

Economic variables are important factors for explaining the dynamics of socio-economic processes and, as a rule, can be reflected in terms of results using abstract models. In conditions of uncertainty and under pressure from the external environment regarding the need to take into account non-economic factors, variables that are related and have a certain correlation with the result can be expressed in different values. To characterize the development processes of socio-economic systems as an object of management, a set of economic-mathematical models is used, among which the following are distinguished: optimization models, models of system dynamics, models of analysis and forecasting of financial reporting, models of discounting and value, conceptual model of ESG management. A structured review of the main generally recognized economic and mathematical methods and models shows that in the process of economic development, the level of technology, production efficiency, investments and other economic and non-economic factors have a certain influence on the direction and trajectory of economic growth, so companies should pay attention to the various influences of factors, to promote more stable development of economic activity. Mathematical models can specify abstract, non-quantitative problems, which is important in terms of sustainable development and the need to take into account non-economic parameters, mostly those that do not have a quantitative dimension. Such factors are difficult to take into account in traditional quantitative economic models. But thanks to the development of conceptual approaches and the use of various tools, the description, reasoning and calculation of relationships between processes and phenomena is possible with the help of quantitative and quantifiable non-quantitative parameters. As a result, economic-mathematical models play an important role in economic research and help solve practical problems on a scientific basis. In theory and in practice, there is a wide arsenal of development management tools. When modeling the company's economic development processes, it is important to consider it as an open socio-economic system consisting of interconnected elements that interact with the external environment. Such a system is presented through the functions performed by the business entity in the process of achieving the set goal, taking into account the conditions and circumstances through the search for possible alternatives. The performance of these functions involves a certain sequence of operations, the optimization of which leads to changes in the socio-economic system, and the actions, limited in time and aimed at the performance of relevant tasks, are modeled taking into account the need to solve problems or form new needs and satisfy potential requests.

Integrated Genetic Algorithm with Dispatching Rules to solve the Flexible Job Shop Scheduling Problem under Multi-AMR Transportation Constraints

The Flexible Job Shop Scheduling Problem (FJSSP) is a challenging issue for industries and manufacturers. However, the transportation tasks in this problem should not be underestimated, as their impact is substantial, and they are frequently overlooked in the literature. In this paper, the FJSSP with multi-AMR (Autonomous mobile robot) transportation constraints is addressed. We developed a genetic algorithm with dispatching rules to solve the Flexible Job Shop Scheduling Problem with Multi-AMR Transportation Constraints by minimizing the total completion time. Two dispatching rules are used to assign transportation robots. The first rule is random assignment and the second rule is AMR per Job assignment. Our encoding and decoding process utilizes a three-layer sequence (machine sequence, operation sequence, and AMR sequence). Finally, we conducted comprehensive experiments on different benchmarks to assess the performance of the proposed algorithm with a variable number of AMR to transport the operations. The experimental results indicate that the proposed algorithm effectively and efficiently solve the problem.

A cooperative evolutionary algorithm with simulated annealing for integrated scheduling of distributed flexible job shops and distribution

Production and distribution are two essential parts in supply chains. An integration of production and distribution has received amount of attention from both academia and industry. This article investigates an integrated scheduling problem of distributed flexible job shops and distribution. First, a mixed integer programming model is developed to minimize maximum completion time. Second, a cooperative evolutionary algorithm with simulated annealing methods is proposed in consideration of the problem's characteristics. A three-link integer string is designed to represent three parts, i.e., factory assignment, machine assignment and operation sequence, in a solution. Three populations are constructed to search the above three parts via genetic operations and simulated annealing methods, respectively. A cooperation strategy is designed to generate a schedule. Then, a heuristic rule is devised to determine the delivery scheme for distribution. Finally, experiments are carried out via extending a set of benchmark instances. The proposed algorithm is compared to four state-of-the-art algorithms and an exact solver CPLEX. The results and discussions verify that the developed model and method have strong competitiveness for solving the considered problems.

Restoration of dilapidated pipeline networks using polymer hoses

The paper considers a set of issues affecting the actual problems of operational repair and restoration work on underground pressure water and drainage pipelines made of various materials that have exhausted their standard service life and are subject to numerous defects in the form of cracks, joint divergences, rust growths, fistulas and others. The aim of the work is to consider trenchless technology as a promising method of repairing dilapidated pipelines, which uses the application of polymer hoses to the inner surface of pipeline networks. The general requirements for flexible polymer sleeves and their characteristics, the scope of application of sleeves, as well as requirements for structural materials used in the production of flexible polymer sleeves are considered as the subject of research. The result of the work is an analysis of the sequence and essence of preparatory operations, including in-line diagnostics and a coding system for the results of visual inspection of pipelines. As conclusions, examples of calculating energy savings during water transportation before and after repair and restoration work at an exemplary facility are given, depending on the technical characteristics of the hoses used, as well as their thickness, depending on the depth of the pipeline.

A Review of the Collection of commented Metarules of Pāṇini's Sanskrit Grammar — "Paribhāṣāvṛtti" by Nīlakaṇṭha Dīkṣita

A while after the compilation of the Sanskrit grammar called "Aṣṭādhyāyī" (≈ V century BC) by the ancient Indian linguist Pāṇini, commentators of this treatise began to formulate numerous metarules guiding to the correct interpretation of grammatical rules. The object of our study are these post-Pāṇinian metarules, also known as paribhāṣās. They describe the metalanguage developed by Panini, varieties of technical use of language’s expressive means in the "Aṣṭādhyāyī", they also help resolve contradictions that arise when reading grammatical rules and settle priorities in the execution sequence of grammatical operations. The material of the study are metarules collected and commented on by the Sanskrit grammarian of the XVII century AD Nīlakaṇṭhadīkṣita in his work "Commentary on paribhāṣās" (Paribhāṣāvṛtti). The purpose of our work is to expose the content of the "Commentary on the paribhāṣās", to classify the metarules collected in this work, to indicate their purpose. The method of the work is a structural and hermeneutical study of the text. For the first time, a detailed analysis of the Nīlakaṇṭhadīkṣita's "Commentary on the paribhāṣās" and the classification of the metarules collected in this work were carried out. For the first time in Russian-language literature, the content of a large number of post-Pāṇinian metarules of Sanskrit grammar "Aṣṭādhyāyī" is exhibited, as well as biographical data about the grammarian Nīlakaṇṭhadīkṣita is revealed.

Effect of Changes in the Sequence of Assembly Operations on Error Rates: A Case Study From the Car Manufacturing Industry

Effect of Changes in the Sequence of Assembly Operations on Error Rates: A Case Study From the Car Manufacturing Industry

Environmental requirements in the standard for acceptance of petroleum products

The article discusses the current state of the process of receiving petroleum products at a gas station in order to eliminate and reduce losses and cycle time. A methodology for preparing a standard for obtaining petroleum products is presented and the effectiveness of its use at a gas station is determined. A standardized sequence of actions made it possible to detect problems and losses and reliably evaluate the efficiency of production processes. Based on the established sequence of operations for the process of receiving petroleum products, the standard work instructions (SWI) indicate the time for performing a separate process operation, the total time of the production cycle, the trajectory of movement through the facility between workplaces, and the classification of work taking into account compliance with safety and environmental requirements. As a result of the redistribution of all operations in order to eliminate and reduce losses and process cycle time, the best sequence of actions was established, which ensured the efficiency of the process of receiving petroleum products and environmental safety during the operation of gas stations.

Algorithm for systematizing information about scientific activities in the environmental education system

The article is devoted to describing the process of collecting and systematizing information about the results of scientific activities in the environmental education system. Carrying out such work is caused by the need to assess the effectiveness of the scientific activities of higher educational institutions that provide training for environmental specialists. Rationalization of the proposed material is carried out using an algorithm, designed in the form of flowcharts, briefly illustrating the content and sequence of operations for collecting and systematizing information.

Development of Fine-Tuned Retrieval Augmented Language Model specialized to manual books on machine tools

This paper aims to reduce potential human errors and loads that arise from the lack of novice human operators and different interfaces in advanced machine tool industries. A digital assistant using generative artificial intelligence is designed to answer questions about machine terminologies, and operation sequences happening in an alarm state. Combining Fine-Tuning, Retrieval Augmented Generation, and Prompt Engineering, it solves problems of common-purpose large language models. The proposed system is implemented on a local server and connected to a mobile device. It shows increasing quantitative accuracy from 51% to 79% and 84% in the fine-tuned and retriever model, and the qualitative score increases from 21 to 25 in the retriever model.

Redesign of Automatic Vacuum Cleaner with Participatory Approach

While using automatic vacuum cleaners, users found dissatisfaction namely dust problem, obstacle problem, and narrow space problem. Therefore, the problems in this automatic vacuum cleaner must be fixed so that it can maximize user productivity. The methods that researchers will use to carry out this research include the participatory ergonomic which is a method for translating consumer needs into an optimal and solutive products by gain aspirations from users and stakeholders. The next method is Maynard Operation Sequence Technique which is a predetermined motion time method that aims to determine the standard time for doing work. There are also participatory usability and ergonomics methods that help this research. For the dust problem, researchers have looked for a solution to the problem, namely by adding SLAM and Artificial Intelligence logarithms to the automatic. For the narrow space problem, researchers have designed different nozzles for the automatic to use. For this exact problem, researchers have added a crevice nozzle to the automatic so that the automatic can insert suction in narrow areas such as the back of cupboards. Researchers created this feature so that users no longer need to bother cleaning dust from sofas, tables and other items in the user’s room.

Real-world validation of a framework for automated knowledge driven feature engineering inspired by medical domain experts

Knowledge discovery from real-world data in health care can be demanding due to unstructured data and low registration quality in electronic health records (EHRs). This requires close collaboration of domain experts and data scientists. To perform the knowledge discovery process more effectively and efficiently, a framework for automatic Knowledge Driven Feature Engineering (aKDFE) has been developed. Central to aKDFE is an automated feature engineering (FE), i.e., an automated construction of new, highly informative variables, referred to as features, from those directly observed and recorded, e.g., in EHRs. The framework learns and aggregates domain knowledge to generate features that are more informative compared to those recorded in EHRs or manually engineered (manual FE) as done in medical research projects today.Manual KDFE is a systematic manual FE process, which improves prediction performance without loss of explainability of the predictions. But the following research questions remained open: (i) is it possible to automate KDFE, (ii) are aKDFE features more informative than features from a manual FE process, and (iii) does aKDFE produce explainable and transparent results?To summarize the present study, aKDFE is (i) more efficient than manual FE since it automates the manual knowledge discovery and FE processes. It is (ii) more effective due to its higher predictive power compared to manual KDFE. This was evaluated on a real-world medical research project by comparing the classification ability when using manual and aKDFE features in machine learning (ML) models, measured as the area under the receiver operating characteristic curve (AUROC). The project included 26,992 patients regarding “Negative bone structure effects of antiepileptic drug consumption”. The baseline features (manual FE) used in studied project were compared with features generated by aKDFE; aKDFE-generated features resulted in higher AUROC than baseline features, with a p-value <0.05. Finally, aKDFE (iii) applies and describes data pivoting and feature generation as explicit and transparent operation sequences on EHR features. Inefficiency issues remain, mainly regarding non-automatic FE and baseline generation.Threat of validity to the aKDFE framework exists in the selection of the pivoting method, the generalization of used FE operations and rules, and usage of evaluation metrics.

Information Entropy Evaluation Method for the Disassemblability of Smartphones

Smartphones are a vast category of consumer electronic products. Design For Disassembly (DFD) is a methodology that can effectively reduce the disassembly, recycling, and maintenance costs of smartphones. However, due to the diverse constraints posed by the connections among smartphone components, the variability of disassembling tools makes it challenging to objectively characterize the disassemblability of the smartphone. Therefore, information entropy is introduced to characterize the complex state of the system. Disassemblability can be expressed by calculating the operating time of the disassembling tool through information entropy. After multiplying by a constrained quantity factor, the Improved Disassembling Tool Entropy (IDTE) responds to changes in disassemblability as the structural level changes. According to the structure and recycling direction, the disassembling level of smartphones can be divided into module level, part level, and hybrid part-module level. Based on the Maynard Operational Sequencing Technique (MOST), the basic unit of operating time of the disassembling tool is calculated. For the hybrid selective Disassembly Sequence Planning (DSP) of the part and module levels, the Improved Double Genetic Algorithm (IDGA) model is established to compute the optimal disassembly sequence corresponding to each program level. This model calculates the IDTE corresponding to the optimal disassembly sequences at each disassembling level. The validity of IDTE was verified by a coupled comparison test between IDTE and theoretical disassembly time. Finally, an analysis of the disassemblability variations was conducted for two different models of smartphones based on their structure.

Layer-based information model for 5-axis milling processes using a GraphQL schema

The view of process-related information in NC-bound manufacturing technologies can range from a perspective of a single cutter location within a considered toolpath to aggregated data which represent the whole operation sequence of a manufacturing process. Data processing pipelines are often individually programmed for the process planning or machining stage addressing an isolated database abstraction layer. This paper proposes a data modeling approach based on a GraphQL schema empowering the user to query planning and actual process data cross-linked with different aggregation layers by a single request.

The Archive of University Science as the Core of Research Education in Russia: the Motivational Potential of Social Software

Social Software as a special kind of organization of goal-oriented joint activity is considered in the present article in the context of cultural-historical epistemology, which is based on the understanding of knowledge as a sign-semiotic, historical phenomenon. This approach, according to the authors, makes it possible to reveal in a new way the educational and pedagogical potential of social software, which today attracts the attention, first of all, of sociologists, political scientists, and economists, who only partially touch upon its cognitive parameters. Meanwhile, appeal to the epistemological dimension of social software allows us to emphasize characteristics that significantly expand the scope of its application, and in particular, the characteristics that open up an additional opportunity to quite effectively motivate students for self-education, for an inherently creative understanding of knowledge as a sociocultural value. The “motivational” potential of social software today is acquiring a particularly important role in the educational structures of “research education”. In such structures, step-by-step software opens up for the student, on the one hand, a sequence of operations that lead research to knowledge as the goal of education, and on the other hand, it dramatically changes in the eyes of students the process of assimilation of information determined by the curriculum, since it involves participation in its “creation”. At the same time, the presence of a social dimension in the software gives cultural and historical meaning to the sequence of students’ efforts, which opens up additional opportunities for motivating their activity through an appeal to the cultural and historical status of the scientific activity within which this knowledge was firstly created. The article demonstrates the experience of implementing one of these opportunities to additionally stimulate the attitude towards self-education through the introduction of philosophy faculties students to archival research of university science in Russia.

Brep2Seq: a dataset and hierarchical deep learning network for reconstruction and generation of computer-aided design models

Abstract Three-dimensional (3D) reconstruction is a significant research topic in the field of computer-aided design (CAD), which is used to recover editable CAD models from original shapes, including point clouds, voxels, meshes, and boundary representations (B-rep). Recently, there has been considerable research interest in deep model generation due to the increasing potential of deep learning methods. To address the challenges of 3D reconstruction and generation, we propose Brep2Seq, a novel deep neural network designed to transform the B-rep model into a sequence of editable parametrized feature-based modeling operations comprising principal primitives and detailed features. Brep2Seq employs an encoder-decoder architecture based on the transformer, leveraging geometry and topological information within B-rep models to extract the feature representation of the original 3D shape. Due to its hierarchical network architecture and training strategy, Brep2Seq achieved improved model reconstruction and controllable model generation by distinguishing between the primary shape and detailed features of CAD models. To train Brep2Seq, a large-scale dataset comprising 1 million CAD designs is established through an automatic geometry synthesis method. Extensive experiments on both DeepCAD and Fusion 360 datasets demonstrate the effectiveness of Brep2Seq, and show its applicability to simple mechanical components in real-world scenarios. We further apply Brep2Seq to various downstream applications, including point cloud reconstruction, model interpolation, shape constraint generation, and CAD feature recognition.

ANALYSIS OF THE COLOR AND ODOR VARIATION OF INDUSTRIAL NEUTRAL DETERGENT: A CASE STUDY

This case study consists of an applied research that aims to identify weaknesses in the processing of neutral detergent responsible for variations in color, odor in a company specialized in sanitation and cleaning products located in Vale do Itajaí/SC. The monitoring of the production process was carried out for three months, evaluating: i) operational items: aptitude, method of execution, standard operating procedures (SOPs) and use of personal protective equipment (PPE); ii) raw material: formulation, quantities and inputs; iii) process water: magnesium, calcium and total hardness. Three preservatives from RDC nº30 and the mixture MIT/CMIT and Bromo-2 Nitro-2 Propanediol (Bronopol) CAS nº52-51-7 tested in this research were evaluated. The productive follow-up demonstrated that the operators were properly trained, carried out activities according to SOPs and used PPE. The preservative content in the formulation was adjusted to 0.28% of the mixture and there was a change in its operational sequence, inserting the thickener after adjusting the pH of the solution. The detergent obtained showed a slightly yellowish color, constant, uniform and without variation in odor after 14 days of elaboration. Physical parameters of the water showed calcium and magnesium hardness &lt;15mg/L and total hardness 16.61mg/L, not interfering with the characteristics of the product or its performance. It is estimate that the problem with the neutral detergent was the preservative used and the operational sequence of preparation of the product, since positive results were obtained in the test formulation, without variation in color and odor after 14 days of preparation.

On Composing Asynchronous Operations

Asynchronous operations are very useful for actions that wait for an external event or work for a long time, to avoid blocking the thread that launches them. Unfortunately, whether they report their termination via callbacks or via completing a future, composing several asynchronous calls is difficult and error prone. The continuations mechanism (provided, for example, in C# Task Parallel Library via ContinueWith()) offers limited support for scheduling a sequence of operations. In this paper we try to improve this mechanism with better support for sequencing operations and exceptions, and with support for conditionals and loops, while covering the specifics of a C++ implementation. The most recent version of our source code is at [14]. Keywords and phrases: asynchronous programming.

Optimizing flexible job shop scheduling with automated guided vehicles using a multi-strategy-driven genetic algorithm

The flexible job scheduling problem with automated guided vehicles (FJSP-AGVs) is a simplified model of some real manufacturing industries. It contains three strongly coupled subproblems: operation sequences assignment, machine selection, and automatic guided vehicle selection, leading to a huge solution space. Its several unresolved challenges, i.e., problem model and algorithmic designing, persist. Therefore, we first adopt the sequence-based modeling method to establish a mixed-integer linear programming model with makespan, and its correctness is verified by using the Gurobi solver. Subsequently, a multi-strategy-driven genetic algorithm (Mult_stra_GA) is proposed based on the implicit features of FJSP-AGVs. In Mult_stra_GA, for the operation sequence (OS) and the machine assignment (MS) subproblems, we design three targeted strategies, i.e., two layer-based encoding and decoding strategy, a multiple heuristics-based initialization strategy, double crossover, and dual mutation operators. Meanwhile, the problem-specific diversity checking and restart strategies are introduced to avoid Mult_stra_GA falling into local optima. Finally, we conduct experiments on four well-known benchmarks. Through the statistical analysis, the outcomes demonstrate that the Mult_stra_GA algorithm exhibits efficacy when contrasted with other advanced algorithms.

MEMORIILE UNOR EROI OLTENI DIN PRIMUL RĂZBOI MONDIAL

As Romania celebrates 100 years since the First World War, The National Archives organized research projects aiming at discovering diaries, memorialist writings, or other contemporary sources. Thus, new, particularly interesting and relevant documents were identified. Among them, two manuscripts from the Service of the National Archives in Vâlcea County are impressive: the Diary of the 1916-Campaign, of Captain Ioan Ciulei, from the Second Vâlcea Infantry Regiment, and the Daily Notes from the Romanian-Hungarian-Bulgarian War in 1916, August 15, recording the memories of sub-lieutenant doctor S. Demetrescu, from the 44th Infantry Regiment. I transcribed the manuscripts in the collection of documents entitled Life on the Front War in Personal Writings, published in 2021. These memorialist writings describe the beginning of the Romanian-Bulgarian-Hungarian hostilities in the Olt valley and in southern Transylvania, the battles at Tălmaci, Cisnădia, Șelimbăr, Poplaca – in the Sibiu area -, the route of doctor S. Demetrescu’s regiment, and the imprisonment of Captain Ioan Ciulei in the German camp on the island of Dänholm. Memorialists mention various military units, officers with initiatives (Brigadier Generals Ion Manolescu, Matei Castriș, Ioan Oprescu, Ioan Popovici, David Praporgescu, Colonel Traian Moșoiu, Lt. Col. Gheorghe Zizi Cantacuzino), the experiences of many soldiers, living or deceased, lists of German camp prisoners, sequences of military operations and their aftermath.