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1

An Energy Efficient and Scalable WSN with Enhanced Data Aggregation Accuracy

Saadallah Noor Raad, Alabady Salah Abdulghani

Journal of Telecommunications and Information Technology

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2024

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nr 2

48--57

EN

This paper introduces a method that combines the K-means clustering genetic algorithm (GA) and Lempel-Ziv-Welch (LZW) compression techniques to enhance the efficiency of data aggregation in wireless sensor networks (WSNs). The main goal of this research is to reduce energy consumption, improve network scalability, and enhance data aggregation accuracy. Additionally, the GA technique is employed to optimize the cluster formation process by selecting the cluster heads, while LZW compresses aggregated data to reduce transmission overhead. To further optimize network traffic, scheduling mechanisms are introduced that contribute to packets being transmitted from sensors to cluster heads. The findings of this study will contribute to advancing packet scheduling mechanisms for data aggregation in WSNs in order to reduce the number of packets from sensors to cluster heads. Simulation results confirm the system's effectiveness compared to other compression methods and non-compression scenarios relied upon in LEACH, M-LEACH, multi-hop LEACH, and sLEACH approaches.

2

Highly efficient scheduling algorithms for identical parallel machines with sufficient conditions for optimality of the solutions

Telenyk Sergii, Nowakowski Grzegorz, Pavlov Oleksandr, Misura Olena, Melnikov Oleg, Khalus Olena

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2024

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Vol. 72, nr 1

art. no. e148939

EN

This paper aims to develop new highly efficient PSC-algorithms (algorithms that contain a polynomial-time sub-algorithm with sufficient conditions for the optimality of the solutions obtained) for several interrelated problems involving identical parallel machine scheduling. These problems share common basic theoretical positions and common principles of their solving. Two main intractable scheduling problems are considered: (“Minimization of the total tardiness of jobs on parallel machines with machine release times and a common due date” (TTPR) and “Minimising the total tardiness of parallel machines completion times with respect to the common due date with machine release times” (TTCR)) and an auxiliary one (“Minimising the difference between the maximal and the minimal completion times of the machines” (MDMM)). The latter is used to efficiently solve the first two ones. For the TTPR problem and its generalisation in the case when there are machines with release times that extend past the common due date (TTPRE problem), new theoretical properties are given, which were obtained on the basis of the previously published ones. Based on the new theoretical results and computational experiments the PSC-algorithm solving these two problems is modified (sub-algorithms A1, A2). Then the auxiliary problem MDMM is considered and Algorithm A0 is proposed for its solving. Based on the analysis of computational experiments, A0 is included in the PSC-algorithm for solving the problems TTPR, TTPRE as its polynomial component for constructing a schedule with zero tardiness of jobs if such a schedule exists (a new third sufficient condition of optimality). Next, the second intractable combinatorial optimization problem TTCR is considered, deducing its sufficient conditions of optimality, and it is shown that Algorithm A0 is also an efficient polynomial component of the PSC-algorithm solving the TTCR problem. Next, the case of a schedule structure is analysed (partially tardy), in which the functionals of the TTPR and TTCR problems become identical. This facilitates the use of Algorithm A1 for the TTPR problem in this case of the TTCR problem. For Algorithm A1, in addition to the possibility of obtaining a better solution, there exists a theoretically proven estimate of the deviation of the solution from the optimum. Thus, the second PSC-algorithm solving the TTCR problem finds an exact solution or an approximate solution with a strict upper bound for its deviation from the optimum. The practicability of solving the problems under consideration is substantiated.

3

Efekt uczenia w harmonogramowaniu wieloobiektowych przedsięwzięć budowlanych z zastosowaniem algorytmu symulowanego wyżarzania

Podolski Michał

Przegląd Budowlany

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2023

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R. 94, nr 1-2

103--107

PL

W artykule przedstawiono problematykę harmonogramowania budowlanych przedsięwzięć wieloobiektowych z uwzględnieniem efektu uczenia. Efekt ten pojawia się podczas wykonywania robót jednego rodzaju w wielu obiektach budowlanych. Doprowadza to do istotnego skrócenia czasu trwania przedsięwzięcia. W prezentowanym modelu przedsięwzięcia istnieje problem poszukiwania optymalnej kolejności wykonywania obiektów, która minimalizuje czas trwania przedsięwzięcia. W artykule zagadnienie to z powodzeniem rozwiązano za pomocą metaheurystycznego algorytmu symulowanego wyżarzania i zilustrowano przykładem praktycznym.

EN

The article presents the issues of scheduling multiunit construction projects, taking into account the learning effect. This effect occurs when one type of the activity is carried out in many building units. This leads to a significant reduction in the duration of the project. In the presented model of the project, there is a problem of searching for the optimal order of execution of the units, which minimizes the duration of the project. In this article, this problem was successfully solved using a metaheuristic simulated annealing algorithm and illustrated by a case study.

4

Analiza wpływu metod intensyfikacji pracy na czas realizacji procesów budowlanych

Rzepecki Łukasz

Przegląd Budowlany

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2023

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R. 94, nr 1-2

88--92

PL

W artykule rozważano problem doboru metod intensyfikacji pracy z uwzględnieniem ich kosztów i efektów w postaci skrócenia czasu trwania procesów budowlanych. Metody te obejmują: pracę w nadgodzinach, pracę w weekendy, pracę na dwie zmiany oraz zatrudnianie bardziej wydajnych brygad roboczych. Opracowano model matematyczny dla powtarzalnych procesów budowlanych, zapewniający minimalizację przerw w pracy brygad oraz redukcję czasu realizacji całego przedsięwzięcia. W celu weryfikacji poprawności modelu opracowane podejście zastosowano do wyznaczenia wariantów organizacyjnych (działań redukujących czas realizacji procesów) dla przykładowego przedsięwzięcia budowlanego.

EN

The paper considers the problem of selecting methods of work acceleration, taking into account their costs and effects in terms of reducing the duration of construction processes. These methods include: working overtime, working on weekends, working in two shifts and employing more efficient work brigades. A mathematical model was developed for repetitive construction processes, ensuring minimization of interruptions in the crews’ work and reduction of the time of the entire project. In order to verify the correctness of the model, the developed approach was used to determine organizational variants (activities that reduce process completion time) for a sample construction project.

5

Optimizing the Job Shop Scheduling Problem with a no Wait Constraint by Using the Jaya Algorithm Approach

Bougloula Aimade Eddine

Management and Production Engineering Review

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2023

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Vol. 14, No. 3

148--155

EN

This work is interested to optimize the job shop scheduling problem with a no wait constraint. This constraint occurs when two consecutive operations in a job must be processed without any waiting time either on or between machines. The no wait job shop scheduling problem is a combinatorial optimization problem. Therefore, the study presented here is focused on solving this problem by proposing strategy for making Jaya algorithm applicable for handling optimization of this type of problems and to find processing sequence that minimizes the makespan (Cmax). Several benchmarks are used to analyze the performance of this algorithm compared to the best-known solutions.

6

Optimization of Job Shop Scheduling Problem by Genetic Algorithms: Case Study

Sahar Habbadi, Herrou Brahim, Sekkat Souhail

Management and Production Engineering Review

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2023

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Vol. 14, No. 3

44--56

EN

The Job Shop scheduling problem is widely used in industry and has been the subject of study by several researchers with the aim of optimizing work sequences. This case study provides an overview of genetic algorithms, which have great potential for solving this type of combinatorial problem. The method will be applied manually during this study to understand the procedure and process of executing programs based on genetic algorithms. This problem requires strong decision analysis throughout the process due to the numerous choices and allocations of jobs to machines at specific times, in a specific order, and over a given duration. This operation is carried out at the operational level, and research must find an intelligent method to identify the best and most optimal combination. This article presents genetic algorithms in detail to explain their usage and to understand the compilation method of an intelligent program based on genetic algorithms. By the end of the article, the genetic algorithm method will have proven its performance in the search for the optimal solution to achieve the most optimal job sequence scenario.

7

Advanced cascaded scheduling for highly autonomous production cells with material flow and tool lifetime consideration using AGVs

Miller Eddi, Engelmann Bastian, Kaupp Tobias, Schmitt Jan

Journal of Machine Engineering

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2023

|

Vol. 23, No. 3

69--85

EN

In today’s manufacturing systems, especially in Industry 4.0, highly autonomous production cells play an important role. To reach this goal of autonomy, different technologies like industrial robots, machine tools, and automated guided vehicles (AGV) are deployed simultaneously which creates numerous challenges on various automation levels. One of those challenges regards the scheduling of all applied resources and their corresponding tasks. Combining data from a real production environment and Constraint Programming (CP-SAT), we provide a cascaded scheduling approach that plans production orders for machine tools to minimize makespan and tool changeover time while enabling the corresponding robot for robot-collaborated processes. Simultaneously, AGVs provide all production cells with the necessary material and tools. Hereby, magazine capacity for raw material as well as finished parts and tool service life are taken into account.

8

Shared-Semaphored Cache Implementation for Parallel Program Execution in Multi-Core Systems

Milik Adam, Walichiewicz Michał

International Journal of Electronics and Telecommunications

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2023

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Vol. 69, No. 2

371--382

EN

The paper brings forward an idea of multi-threaded computation synchronization based on the shared semaphored cache in the multi-core CPUs. It is dedicated to the implementation of multi-core PLC control, embedded solution or parallel computation of models described using hardware description languages. The shared semaphored cache is implemented as guarded memory cells within a dedicated section of the cache memory that is shared by multiple cores. This enables the cores to speed up the data exchange and seamlessly synchronize the computation. The idea has been verified by creating a multi-core system model using Verilog HDL. The simulation of task synchronization methods allows for proving the benefits of shared semaphored memory cells over standard synchronization methods. The proposed idea enhances the computation in the algorithms that consist of relatively short tasks that can be processed in parallel and requires fast synchronization mechanisms to avoid data race conditions.

9

Multi-objective optimization model for a multi-depot mixed fleet electric vehicle scheduling problem with real-world constraints

Duda Jerzy, Karkula Marek, Puka Radosław, Skalna Iwona, Fierek Szymon, Redmer Adam, Kisielewski Piotr

Transport Problems

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2022

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T. 17, z. 4

137--149

EN

This paper presents the problem of public transport planning in terms of the optimal use of the available fleet of vehicles and reductions in operational costs and environmental impact. The research takes into account the large fleet of vehicles of various types that are typically found in large cities, including the increasingly widely used electric buses, many depots, and numerous limitations of urban public transport. The mathematical multi-criteria mathematical model formulated in this work considers many important criteria, including technical, economic, and environmental criteria. The preliminary results of the Mixed Integer Linear Programming solver for the proposed model on both theoretical data and real data from urban public transport show the possibility of the practical application of this solver to the transport problems of medium-sized cities with up to two depots, a heterogeneous fleet of vehicles, and up to about 1500 daily timetable trips. Further research directions have been formulated with regard to larger transport systems and new dedicated heuristic algorithms.

10

Multi-criteria human resources planning optimisation using genetic algorithms enhanced with MCDA

Jurczak Marcin, Miebs Grzegorz, Bachorz Rafał A.

Operations Research and Decisions

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2022

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Vol. 32, No. 4

57--74

EN

The main objective of this paper is to present an example of the IT system implementation with advanced mathematical optimisation for job scheduling. The proposed genetic procedure leads to the Pareto front, and the application of the multiple criteria decision aiding (MCDA) approach allows extraction of the final solution. Definition of the key performance indicator (KPI), reflecting relevant features of the solutions, and the efficiency of the genetic procedure provide the Pareto front comprising the representative set of feasible solutions. The application of chosen MCDA, namely elimination et choix traduisant la réalité (ELECTRE) method, allows for the elicitation of the decision maker (DM) preferences and subsequently leads to the final solution. This solution fulfils all of the DM expectations and constitutes the best trade-off between considered KPIs. The proposed method is an efficient combination of genetic optimisation and the MCDA method.

11

Zastosowanie metody sprzężeń czasowych TCM 1 w harmonogramowaniu robót budowlanych

Rogalska Magdalena, Hejducki Zdzisław

Materiały Budowlane

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2022

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nr 12

56--58

PL

W artykule przedstawiono sposób wykonania harmonogramu w postaci wykresu Gantta z zastosowaniem szeregowania zadań metodą sprzężeń czasowych i ciągłości pracy TCM 1 brygad roboczych. Tradycyjną metodą wizualizacji harmonogramu w TCM są cyklogramy. W artykule przedstawiono wykorzystanie programu MS Project do wykonania wykresów Gantta z zastosowaniem szeregowania zadań metodą TCM 1 ze względu na możliwość wykorzystania tego programu w analizie ryzyka i kosztów cyklu życia budowli, gdzie konieczne jest zastosowanie wykresu Gantta do obliczeń.

EN

The purpose of this work is to present the method of making a schedule in the form of a Gantt chart with the use of task scheduling using the time coupling method while maintaining the continuity of work of TCM 1 working teams. The traditional method of schedule visualization in TCM are cyclograms, in this work MS Project was used to prepare Gantt charts using the TCM 1 task scheduling method due to the need to use this program in the risk and cost analysis of the building life cycle, where it is necessary to use the Gantt chart to calculations.

12

Prioritizing and Scheduling of Production Orders in Non-homogenous Production Systems

Skołud Bożena, Szopa Agnieszka, Kalinowski Krzysztof

Management and Production Engineering Review

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2022

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Vol. 13, No. 1

62--75

EN

The aim of the work was to develop a prioritizing and scheduling method to be followed in small and medium-sized companies operating under conditions of non-rhythmic and nonrepeatable production. A system in which make to stock, make to order and engineer to order (MTS, MTO and ETO) tasks are carried out concurrently, referred to as a non-homogenous system, has been considered. Particular types of tasks have different priority indicators. Processes involved in the implementation of these tasks are dependent processes, which compete for access to resources. The work is based on the assumption that the developed procedure should be a universal tool that can be easily used by planners. It should also eliminate the intuitive manner of prioritizing tasks while providing a fast and easy to calculate way of obtaining an answer, i.e. a ready plan or schedule. As orders enter the system on an ongoing basis, the created plan and schedule should enable fast analysis of the result and make it possible to implement subsequent orders appearing in the system. The investigations were based on data from the non-homogenous production system functioning at the Experimental Plant of the Łukasiewicz Research Network – Institute of Ceramics and Building Materials, Refractory Materials Division – ICIMB. The developed procedure includes the following steps: 1 – Initial estimation of resource availability, 2 – MTS tasks planning, 3 – Production system capacity analysis, 4 – ETO tasks planning, 5 – MTO orders planning, 6 – Evaluation of the obtained schedule. The scheduling procedure is supported by KbRS (Knowledge-based Rescheduling System), which has been modified in functional terms for the needs of this work assumption.

13

Input Sequence of Jobs on NEH Algorithm for Permutation Flowshop Scheduling Problem

Puka Radosław, Duda Jerzy, Stawowy Adam

Management and Production Engineering Review

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2022

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Vol. 13, No. 1

32--43

EN

One of the most popular heuristics used to solve the permutation flowshop scheduling problem (PFSP) is the NEH algorithm. The reasons for the NEH popularity are its simplicity, short calculation time, and good-quality approximations of the optimal solution for a wide range of PFSP instances. Since its development, many works have been published analysing various aspects of its performance and proposing its improvements. The NEH algorithm includes, however, one unspecified and unexamined feature that is related to the order of jobs with equal values of total processing time in an initial sequence. We examined this NEH aspect using all instances from Taillard’s and VRF benchmark sets. As presented in this paper, the sorting operation has a significant impact on the results obtained by the NEH algorithm. The reason for this is primarily the input sequence of jobs, but also the sorting algorithm itself. Following this observation, we have proposed two modifications of the original NEH algorithm dealing with sequencing of jobs with equal total processing time. Unfortunately, the simple procedures used did not always give better results than the classical NEH algorithm, which means that the problem of sequencing jobs with equal total processing time needs a smart approach and this is one of the promising directions for further research.

14

An Intelligent Method for the Scheduling of Cyber Physical Production Systems

Khadiri Hassan, Sekkat Souhail, Herrou Brahim

Management and Production Engineering Review

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2022

|

Vol. 13, No. 1

44--51

EN

The new industrial era, industry 4.0, leans on Cyber Physical Systems CPS. It is an emergent approach of Production System design that consists of the intimate integration between physical processes and information computation and communication systems. The CPSs redefine the decision-making process in shop floor level to reach an intelligent shop floor control. The scheduling is one of the most important shop floor control functions. In this paper, we propose a cooperative scheduling based on multi-agents modelling for Cyber Physical Production Systems. To validate this approach, we describe a use case in which we implement a scheduling module within a flexible machining cell control tool.

15

A feasible schedule for parallel assembly tasks in flexible manufacturing systems

Majdzik Paweł

International Journal of Applied Mathematics and Computer Science

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2022

|

Vol. 32, no. 1

51--63

EN

The paper concerns the design of a framework for implementing fault-tolerant control of hybrid assembly systems that connect human operators and fully automated technical systems. The main difficulty in such systems is related to delays that result from objective factors influencing human operators’ work, e.g., fatigue, experience, etc. As the battery assembly system can be considered a firm real-time one, these delays are treated as faults. The presented approach guarantees real-time compensation of delays, and the fully automated part of the system is responsible for this compensation. The paper begins with a detailed description of a battery assembly system in which two cooperating parts can be distinguished: fully automatic and semi-automatic. The latter, nonderministic in nature, is the main focus of this paper. To describe and analyze the states of the battery assembly system, instead of the most commonly used simulation, the classic max-plus algebra with an extension allowing one to express non-deterministic human operators’ work is used. In order to synchronize tasks and schedule (according to the reference schedule) automated and human operators’ tasks, it is proposed to use a wireless IoT platform called KIS.ME. As a result, it allows a reference model of human performance to be defined using fuzzy logic. Having such a model, predictive delays tolerant planning is proposed. The final part of the paper presents the achieved results, which clearly indicate the potential benefits that can be obtained by combining the wireless KIS.ME architecture (allocated in the semi-automatic part of the system) with wired standard production networks.

16

A New Model for Scheduling Operations in Modern Agricultural Processes

Noer Zulhery, Elveny Marischa, Jalil Abduladheem Turki, Iswanto A. Heri, Al-Janabi Samaher, Alkaim Ayad F., Mullagulova Gulnara, Nikolaeva Natalia, Shichiyakh Rustem Adamovich

Foundations of Computing and Decision Sciences

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2022

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Vol. 47, No. 2

151--161

EN

In recent years, the increase in population and the decrease in agricultural lands and water shortages have caused many problems for agriculture and farmers. That is why scheduling is so important for farmers. Therefore, the implementation of an optimal schedule will lead to better use of agricultural land, reduce water consumption in agriculture, increase efficiency and quality of agricultural products. In this research, a scheduling problem for harvesting agricultural products has been investigated. InPaper this problem, there are n number of agricultural lands that in each land m agricultural operations are performed by a number of machines that have different characteristics. This problem is modeled as a scheduling problem in a flexible workshop flow environment that aims to minimize the maximum completion time of agricultural land. The problem is solved by programming an integer linear number using Gams software. The results show that the proposed mathematical model is only capable of solving small and medium-sized problems, and due to the Hard-NP nature of the problem, large-scale software is not able to achieve the optimal solution.

17

Firefly algorithm applied to the job-shop scheduling problem

Świtalski Piotr, Bolesta Arkadiusz

Studia Informatica : systems and information technology

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2021

|

Vol. 1-2(25)

87--100

EN

The job shop scheduling problem (JSSP) is one of the most researched scheduling problems. This problem belongs to the NP-hard class. An optimal solution for this category of problems is rarely possible. We try to find suboptimal solutions using heuristics or metaheuristics. The firefly algorithm is a great example of a metaheuristic. In this paper, this algorithm is used to solve JSSP. We used some benchmarking JSSP datasets for experiments. The experimental program was implemented in the aitoa library. We investigated the optimal parameter settings of this algorithm in terms of JSSP. Analysis of the experimental results shows that the algorithm is useful to solve scheduling problems.

18

Harmonogramowanie powtarzalnych procesów budowlanych z zastosowaniem algorytmu rojowego

Tomczak Michał, Jaśkowski Piotr

Przegląd Budowlany

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2021

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R. 92, nr 7-8

45--49

PL

W artykule zaproponowano metodę optymalizacji trójkryterialnej harmonogramów powtarzalnych procesów budowlanych. Ze względu na trudności w projektowaniu realizacji tego typu przedsięwzięć z wykorzystaniem klasycznych narzędzi i metod zaproponowano wykorzystanie algorytmów rojowych do znajdowania niezdominowanych rozwiązań problemu. Zaprezentowano także przykład zastosowania algorytmu optymalizacji rojem cząstek do opracowania harmonogramu realizacji powtarzalnych procesów budowlanych i doboru brygad roboczych w celu minimalizacji czasu realizacji przedsięwzięcia i poszczególnych obiektów lub działek roboczych oraz przestojów w pracy brygad.

EN

This paper proposes a method for tri-criteria optimization of schedules of repetitive construction processes. Due to the difficulties in designing the implementation of such projects using classical tools and methods, the use of swarm algorithms for finding non-dominated solutions to the problem was proposed. An example of the application of the particle swarm optimization algorithm to the development of a schedule for the realization of repetitive construction processes and the selection of work crews in order to minimize the execution time of the project and individual objects or work units as well as downtime in the work crews is also presented.

19

Parametric Schedulability Analysis of a Launcher Flight Control System under Reactivity Constraints.

André Étienne, Coquard Emmanuel, Fribourg Laurent, Jerray Jawher, Lesens David, Keller Jörg, Penczek Wojciech

Fundamenta Informaticae

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2021

|

Vol. 182, nr 1

31--67

EN

The next generation of space systems will have to achieve more and more complex missions. In order to master the development cost and duration of such systems, an alternative to a manual design is to automatically synthesize the main parameters of the system. In this paper, we present an approach for the specific case of the scheduling of the flight control of a space launcher. The approach requires two successive steps: (1) the formalization of the problem to be solved in a parametric formal model and (2) the synthesis of the model parameters with a tool. We first describe the problem of the scheduling of a launcher flight control, then we show how this problem can be formalized with parametric stopwatch automata; we then present the results computed by the parametric timed model checker IMITATOR. We enhance our model by taking into consideration the time for switching context, and we compare the results to those obtained by other tools classically used in scheduling.

20

Explicit modeling of multi-period setup times in proportional lot-sizing and scheduling problem with variable capacity

Kaczmarczyk Waldemar

Archives of Control Sciences

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2021

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Vol. 31, No. 4

883--912

EN

Small bucket models with many short fictitious micro-periods ensure high-quality schedules in multi-level systems, i.e., with multiple stages or dependent demand. In such models, setup times longer than a single period are, however, more likely. This paper presents new mixed-integer programming models for the proportional lot-sizing and scheduling problem (PLSP) with setup operations overlapping multiple periods with variable capacity. A new model is proposed that explicitly determines periods overlapped by each setup operation and the time spent on setup execution during each period. The model assumes that most periods have the same length; however, a few of them are shorter, and the time interval determined by two consecutive shorter periods is always longer than a single setup operation. The computational experiments show that the new model requires a significantly smaller computation effort than known models.