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1

The solution of MRSLP with the use of heuristic algorithms

Kochańska Joanna, Burduk Anna, Łapczyńska Dagmara, Musiał Kamil

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2024

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Vol. 72, nr 1

art. no. e146407

EN

Improving production processes includes not only activities concerning manufacturing itself, but also all the activities that are necessary to achieve the main objectives. One such activity is transport, which, although a source of waste in terms of adding value to the product, is essential to the realization of the production process. Over the years, many methods have been developed to help manage supply and transport in such a way as to reduce it to the necessary minimum. In the paper, the problem of delivering components to a production area using trains and appropriately laid-out carriages was described. It is a milk run stop locations problem (MRSLP), whose proposed solution is based on the use of heuristic algorithms. Intelligent solutions are getting more and more popular in the industry because of the possible advantages they offer, especially those that include the possibility of finding an optimum local solution in a relatively short time and the prevention of human errors. In this paper, the applicability of three algorithms – tabu search, genetic algorithm, and simulated annealing – was explored.

2

Efficient Maritime Healthcare Resource Allocation Using Reinforcement Learning

Hasan Tehreem, Batool Farwa, Fiorino Mario, Tretola Giancarlo, Abbas Musarat

Annals of Computer Science and Information Systems

|

2024

|

Vol. 39

615--620

EN

The allocation of healthcare resources on ships is crucial for safety and well-being due to limited access to external aid. Proficient medical staff on board provide a mobile healthcare facility, offering a range of services from first aid to complex procedures. This paper presents a system model utilizing Reinforcement Learning (RL) to optimize doctor-patient assignments and resource allocation in maritime settings. The RL approach focuses on dynamic, sequential decision-making, employing Q-learning to adapt to changing conditions and maximize cumulative rewards. Our experimental setup involves a simulated healthcare environment with variable patient conditions and doctor availability, operating within a 24-hour cycle. The Q-learning algorithm iteratively learns optimal strategies to enhance resource utilization and patient outcomes, prioritizing emergency cases while balancing the availability of medical staff. The results highlight the potential of RL in improving healthcare delivery on ships, demonstrating the system's effectiveness in dynamic, time-constrained scenarios and contributing to overall maritime safety and operational resilience.

3

An Improved Genetic Algorithm for Set Cover using Rosenthal Potential

Tayebi Dena, Ray Saurabh, Ajwani Deepak

Annals of Computer Science and Information Systems

|

2024

|

Vol. 39

689--694

EN

A major issue with heuristics for set-cover problem is that they tend to get stuck in a local optimum typically because a large local move is necessary to find a better solution. A recent theoretical result shows that replacing the objective function by a proxy (which happens to be Rosenthal potential function) allows escaping such local optima even with small local moves albeit at the cost of an approximation factor. The Rosenthal potential function thus has the effect of smoothing the optimization landscape appropriately so that local search works. In this paper, we use this theoretical insight to design a simple but robust genetic algorithm for weighted set cover. We modify the fitness function as well as the crossover operator of the genetic algorithm to leverage the Rosenthal potential function. We show empirically this greatly improves the quality of the solutions obtained especially in examples where large local moves are required. Our results are better than existing state of the art genetic algorithms and also comparable in performance with the recent local search algorithm NuSC (carefully engineered for set cover) on benchmark instances. Our algorithm, however, performs better than NuSC on simple synthetic instances where starting from an initial solution, large local moves are necessary to find a solution that is close to optimal. For such instances, our algorithm is able to find near optimal solutions whereas NuSC either takes a very long time or returns a much worse solution.

4

A novel hybrid cuckoo search algorithm for optimization of a line-start PM synchronous motor

Knypiński Łukasz

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2023

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Vol. 71, nr 1

art. no. e144586

EN

The paper presents a novel hybrid cuckoo search (CS) algorithm for the optimization of the line-start permanent magnet synchronous motor (LSPMSM). The hybrid optimization algorithm developed is a merger of the heuristic algorithm with the deterministic Hooke–Jeeves method. The hybrid optimization procedure developed was tested on analytical benchmark functions and the results were compared with the classical cuckoo search algorithm, genetic algorithm, particle swarm algorithm and bat algorithm. The optimization script containing a hybrid algorithm was developed in Delphi Tiburón. The results presented show that the modified method is characterized by better accuracy. The optimization procedure developed is related to a mathematical model of the LSPMSM. The multi-objective compromise function was applied as an optimality criterion. Selected results were presented and discussed.

5

A hybrid model of heuristic algorithm and gradient descent to optimize neural networks

Mirkhan Amer, Çelebi Numan

Bulletin of the Polish Academy of Sciences. Technical Sciences

|

2023

|

Vol. 71, nr 6

art. no. e147924

EN

Training a neural network can be a challenging task, particularly when working with complex models and large amounts of training data, as it consumes significant time and resources. This research proposes a hybrid model that combines population-based heuristic algorithms with traditional gradient-based techniques to enhance the training process. The proposed approach involves using a dynamic population-based heuristic algorithm to identify good initial values for the neural network weight vector. This is done as an alternative to the traditional technique of starting with random weights. After several cycles of distributing search agents across the search domain, the training process continues using a gradient-based technique that starts with the best initial weight vector identified by the heuristic algorithm. Experimental analysis confirms that exploring the search domain during the training process decreases the number of cycles needed for gradient descent to train a neural network. Furthermore, a dynamic population strategy is applied during the heuristic search, with objects added and removed dynamically based on their progress. This approach yields better results compared to traditional heuristic algorithms that use the same population members throughout the search process.

6

Automatic code optimization for computing the McCaskill partition functions

Bielecki Wlodzimierz, Palkowski Marek, Poliwoda Maciej

Annals of Computer Science and Information Systems

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2022

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Vol. 30

475--478

EN

In this paper, we present the application of three automatic source-to-source compilers to code implementing McCaskill's bioinformatics algorithm. It computes propabilities of various substructures for RNA prediction. McCaskill's algorithm is compute and data intensive and it is within dynamic programming. A corresponding programming code exposes non-uniform dependences that complicates tiling of that code. The corresponding code is represented within the polyhedral model. Its optimization is still a challenging task for optimizing compilers employing multi-threaded loop tiling. To generate optimized code, we used the popular PLuTo compiler that finds and applies affine transformations, the TRACO compiler based on calculating the transitive closure of loop dependence graphs, and the newest polyhedral tool DAPT implementing space-time tiling. An experimental study fulfilled on two multi-core machines: an AMD Epyc with 64 threas and a 2x Intel Xeon Platinum 9242 with 192 threads demonstrates considerable speedup, high locality, and scalability for various problem sizes and the number of threads of generated codes by means of space-time tiling.

7

Constrained optimization of line-start PM motor based on the gray wolf optimizer

Knypińskia Łukasz

Eksploatacja i Niezawodność

|

2021

|

Vol. 23, no. 1

1--10

EN

This paper presents the algorithm and computer software for constrained optimization based on the gray wolf algorithm. The gray wolf algorithm was combined with the external penalty function approach. The optimization procedure was developed using Borland Delphi 7.0. The developed procedure was then applied to design of a line-start PM synchronous motor. The motor was described by three design variables which determine the rotor structure. The multiplicative compromise function consisted of three maintenance parameters of designed motor and one non-linear constraint function was proposed. Next, the result obtained for the developed procedure (together with the gray wolf algorithm) was compared with results obtained using: (a) the particle swarm optimization algorithm, (b) the bat algorithm and (c) the genetic algorithm. The developed optimization algorithm is characterized by good convergence, robustness and reliability. Selected results of the computer simulation are presented and discussed.

8

Allocation of real power generation based on computing over all generation cost: an approach of Salp Swarm Algorithm

Devarapalli Ramesh, Sinha Nikhil Kumar, Rao Bathina Venkateswara, Knypiński Łukasz, Lakshmi Naraharisetti Jaya Naga, García Márquez Fausto Pedro

Archives of Electrical Engineering

|

2021

|

Vol. 70, nr 2

337--349

EN

Economic Load Dispatch (ELD) is utilized in finding the optimal combination of the real power generation that minimizes total generation cost, yet satisfying all equality and inequality constraints. It plays a significant role in planning and operating power systems with several generating stations. For simplicity, the cost function of each generating unit has been approximated by a single quadratic function. ELD is a subproblem of unit commitment and a nonlinear optimization problem. Many soft computing optimization methods have been developed in the recent past to solve ELD problems. In this paper, the most recently developed population-based optimization called the Salp Swarm Algorithm (SSA) has been utilized to solve the ELD problem. The results for the ELD problem have been verified by applying it to a standard 6-generator system with and without due consideration of transmission losses. The finally obtained results using the SSA are compared to that with the Particle Swarm Optimization (PSO) algorithm. It has been observed that the obtained results using the SSA are quite encouraging.

9

Heuristic algorithm to predict the location of C0 separators for efficient isogeometric analysis simulations with direct solvers

Paszyńska A., Jopek K., Woźniak M., Paszyński M.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2018

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Vol. 66, nr 6

907--917

EN

We focus on two and three-dimensional isogeometric finite element method computations with tensor product Ck B-spline basis functions. We consider the computational cost of the multi-frontal direct solver algorithm executed over such tensor product grids. We present an algorithm for estimation of the number of floating-point operations per mesh node resulting from the execution of the multi-frontal solver algorithm with the ordering obtained from the element partition trees. Next, we propose an algorithm that introduces C0 separators between patches of elements of a given size based on the stimated number of flops per node. We show that the computational cost of the multi-frontal solver algorithm executed over the computational grids with C0 separators introduced is around one or two orders of magnitude lower, while the approximability of the functional space is improved. We show O(NlogN) computational complexity of the heuristic algorithm proposing the introduction of the C0 separators between the patches of elements, reducing the computational cost of the multi-frontal solver algorithm.

10

Matematyczny model izolacji usług w sieciach plastrowych

Nowak T.

Przegląd Telekomunikacyjny + Wiadomości Telekomunikacyjne

|

2017

|

nr 8-9

872--875, CD

PL

W pracy przedstawiono koncepcję modelowania podziału sieci na izolowane plastry, które realizują usługi dla użytkowników. Przedstawiono podstawowe kryteria przydziału usług do plastrów z uwzględnieniem izolacji między usługami, które następnie wyrażono za pomocą modelu matematycznego. Zaproponowano algorytm heurystyczny, który rozwiązuje problem przydziału usług do plastrów z uwzględnieniem parametrów QoS.

EN

In this paper, the concept of Network Slicing with isolated slices was shown. The main criteria for selecting services into slices was described in mathematical model which contains isolation constrains for services. For solving problem defined by mathematical model was proposed heuristic algorithm, which solves problem of attaching services to slices with proper QoS values.

11

A random search algorithm for cyclic delivery synchronization problem

Gdowska K., Książek R.

LogForum

|

2017

|

Vol. 13, no. 3

263--272

EN

Background: The paper is devoted to the cyclic delivery synchronization problem with vehicles serving fixed routes. Each vehicle is assigned to a fixed route: the series of supplier’s and logistic centers to be visited one after another. For each route the service frequency is fixed and known in advance. A vehicle loads at a supplier’s, then it delivers goods to a logistic center and either loads other goods there and delivers them to the next logistic center along the route or goes to another logistic center. Each logistic center can belong to several routes, so goods are delivered there with one vehicle and then they departure for the further journey with another truck. The objective of this cyclic delivery synchronization problem is to maximize the total number of synchronizations of vehicles arrivals in logistic centers and their load times, so that it is possible to organize their arrivals in repeatable blocks. Methods: Basing on the previously developed mathematical model for the cyclic delivery synchronization problem we built a random search algorithm for cyclic delivery synchronization problem. The random heuristic search utilizes objective-oriented randomizing. In the paper the newly-developed random search algorithm for cyclic delivery synchronization problem is presented. Results: A computational experiment consisted of employing the newly-developed random search algorithm for solving a series of cyclic delivery synchronization problems. Results obtained with the algorithm were compared with solutions computed with the exact method. Conclusions: The newly-developed random search algorithm for cyclic delivery synchronization problem gives results which are considerably close to the ones obtained with mixed-integer programming. The main advantage of the algorithm is reduction of computing time; it is relevant for utilization of this method in practice, especially for large-sized problems.

PL

Wstęp: W pracy przedstawiono problem synchronizowania dostaw cyklicznych do centrów przeładunkowych. Dostawy realizowane są na stałych trasach: pojazd, obsługujący daną trasę ma dostarczyć towar do centrum przeładunkowego, załadować tam inny towar i przewieźć go do kolejnego punktu trasy lub wykonać pusty przejazd do punktu załadunku. Punktami synchronizacji obsługi tras są centra logistyczne, w których niejednokrotnie towar przywieziony przez jeden pojazd, wyrusza w dalszą drogę innym. Dostawy na każdej trasie realizowane są ze stałą częstotliwością. Trasy dostaw oraz ilości przewożonego towaru są znane. Celem w zadaniu synchronizacji dostaw cyklicznych jest maksymalizacja liczby synchronizacji przyjazdów i pobytu pojazdów w centrach logistycznych tak, aby możliwe było grupowanie ich obsługi w bloki rozładunkowo-załadunkowe. Metody: Na podstawie opracowanego wcześniej modelu matematycznego dla problemu synchronizowania dostaw cyklicznych do centrów przeładunkowych został zbudowany algorytm heurystyczny poszukujący rozwiązań poprzez ukierunkowane losowanie. W artykule przedstawiono opracowany algorytm losowego przeszukiwania. Wyniki: Eksperyment obliczeniowy polegał na rozwiązaniu zestawu zadań synchronizowania dostaw cyklicznych przy pomocy opracowanego algorytmu i porównaniu uzyskanych wyników ze znanymi rozwiązaniami dokładnymi. Wnioski: Przedstawiony algorytm heurystyczny dla zadania synchronizowania dostaw cyklicznych pozwala na uzyskanie rozwiązań zbliżonych do wyników otrzymanych przy zastosowaniu modelu programowania matematycznego. Zaletą zastosowanego algorytmu jest znaczne skrócenie czasu poszukiwania rozwiązania, co może mieć znaczenie dla praktycznego wykorzystania zaproponowanej metody.

12

Multi criterion multicast routing algorithm comparison for large networks

Stachowiak K.

Image Processing & Communications

|

2017

|

Vol. 22, no. 1

49--55

EN

QoS enabled multicast routing is known to be of non-polynominal complexity, which leads to the necessity of using heuristic algorithms to ﬁnd sub-optimal solutions to the problems of this class. The evaluation of such algorithms requires the use of the simulation techniques as the heuristics’ results are of stochastic nature. Because of the problem complexity the simulation times increase signiﬁcantly in the function of the network size, therefore the results presented in the literature are often limited to only small models. In this article the results of the evaluation of different multicast QoS routing algorithms (further referred to as the Multi-Constrained Minimum Steiner Tree Problem-MCMST)have been presented for a wide range of network sizes reaching thousands of nodes.

13

Utilization Balancing Algorithms for Dynamic Multicast Scheduling Problem in EON

Markowski M.

International Journal of Electronics and Telecommunications

|

2016

|

Vol. 62, No. 4

363--370

EN

Dynamic data transfer demands are often being a challenge for present communication networks, as they appear in unpredictable time and must be satisfied prior to deadline. Important kind are the multi-target demands occurring in task of replication, backup, database synchronization or file transferring in pear-to-pear networks. Optimal scheduling usually depends of the nature of transport network. In the paper dynamic deadlinedriven multicast scheduling problem over elastic optical network is considered. Particularly, the method for improving link utilization by traffic balance for multicast demands is proposed. Few heuristic algorithms and results of experiments, proving the benefits of balancing concept are presented

14

Exact and heuristic approaches to solve the Internet shopping optimization problem with delivery costs

Lopez-Loces M. C., Musial J., Pecero J. E., Fraire-Huacuja H. J., Blazewicz J., Bouvry P.

International Journal of Applied Mathematics and Computer Science

|

2016

|

Vol. 26, no. 2

391--406

EN

Internet shopping has been one of the most common online activities, carried out by millions of users every day. As the number of available offers grows, the difficulty in getting the best one among all the shops increases as well. In this paper we propose an integer linear programming (ILP) model and two heuristic solutions, the MinMin algorithm and the cellular processing algorithm, to tackle the Internet shopping optimization problem with delivery costs. The obtained results improve those achieved by the state-of-the-art heuristics, and for small real case scenarios ILP delivers exact solutions in a reasonable amount of time.

15

Evolutionary algorithm for minmax regret flow-shop problem

Ćwik M., Józefczyk J.

Management and Production Engineering Review

|

2015

|

Vol. 6, No. 3

3--9

EN

The uncertain flow-shop is considered. It is assumed that processing times are not given a priori, but they belong to intervals of known bounds. The absolute regret (regret) is used to evaluate a solution (a schedule) which gives the minmax regret binary optimization problem. The evolutionary heuristic solution algorithm is experimentally compared with a simple middle interval heuristic algorithm for three machines instances. The conducted simulations confirmed the several percent advantage of the evolutionary approach.

16

Methodology of Optimization of the Design of an Orthopedic Implant

Muzalewska M., Moczulski W.

Machine Dynamics Research

|

2015

|

Vol. 39, No. 2

133-141

EN

The scientific goal of the project is multicriterial optimization of the design of an orthopedic implant responsible for supporting the reconstruction of the anterior cruciate ligament. The implant should not only precisely anchor the tendon in the tunnel but, above all, - thanks to appropriately selected geometric shape and other design features - accelerate the ingrowth of bone tissue into the grafted tendon. The condition for the correct ingrowth of the bone tissue is to enable optimal perfusion of blood and other body fluids into the ligament prosthesis (grafted tendon). Therefore, the geometrical shape of the implant should allow accumulating active biological factors in the vicinity of the grafted tendon, thus accelerating the healing process. The research hypothesis is that there is a specific number of holes of a certain shape and a specific arrangement of these holes, which ensure optimum blood perfusion by maintaining adequate mechanical properties. Finding the optimum is possible by methods such as Artificial Immune Systems from heuristic algorithms class.

17

Zastosowanie algorytmu hybrydowego do wyznaczenia przydziału pojazdów do zadań w przedsiębiorstwach usług komunalnych

Izdebski M., Jacyna M.

Logistyka

|

2015

|

nr 4

321--332

PL

W artykule przedstawiono problem przydziału pojazdów do zadań w przedsiębiorstwach usług komunalnych oraz model matematyczny problemu przydziału. Opisano metodę rozwiązującą omawiane zagadnienie oraz zaproponowano algorytm hybrydowy rozwiązujący zagadnienia optymalizacyjne przedstawionej metody. Algorytm hybrydowy jest kombinacją algorytmu genetycznego i mrówkowego. Algorytm mrówkowy generuje populację początkową dla algorytmu genetycznego. Wyniki algorytmu hybrydowego porównano z wynikami algorytmu mrówkowego, genetycznego z losową populacją początkową i algorytmu przeszukiwania losowego.

EN

This paper presents the assignment problem of vehicles to tasks in municipal services companies and the mathematical model of this problem. The article describes the method solving the discussed issue and proposes the hybrid algorithm solving the optimization problems of the presented method. The hybrid algorithm is a combination of the genetic and ant algorithm. The ant algorithm generates the initial population for the genetic algorithm. Results of the hybrid algorithm were compared with results of the ant algorithm, the genetic algorithm with the initial population selected randomly and random search algorithm.

18

Dependence of mobile robot task scheduling on fitness functions

Miczulski W., Powroźnik P.

Przegląd Elektrotechniczny

|

2014

|

R. 90, nr 7

43--47

EN

The results of simulation studies designed to assess two of the fitness functions (Or1 and Or2) for the GRASP algorithm used in the elastic scheduling task model (ESTM) have been presented in the paper. The obtained results indicate that the GRASP algorithm with the fitness function Or2 was better at choosing new settings for Tsel to exploit the hardware resources of a mobile robot. Furthermore, it has been found that for Or2 new settings for Tsel are closer to Tnom than Tmax (task cycle execution is reduced which enables a quicker response of a mobile robot to events).

PL

W artykule przedstawiono wyniki badań symulacyjnych umożliwiających ocenę dwóch opracowanych funkcji celu (Or1 i Or2) dla algorytmu GRASP zastosowanego w elastycznym modelu szeregowania zadań. Otrzymane wyniki badań wskazują, że dla funkcji celu Or2 nowe nastawy Tsel lepiej dopasowały wykorzystanie zasobów sprzętowych robota mobilnego do założonej wartości. Ponadto dla Or2 stwierdzono bliższy dobór wartości Tsel do Tnom niż Tmax (cykl wykonywania zadań skraca się, przez co robot mobilny może szybciej reagować na zdarzenia).

19

Heuristic Rating Estimation Approach to The Pairwise Comparisons Method

Kułakowski K.

Fundamenta Informaticae

|

2014

|

Vol. 133, nr 4

367--386

EN

The Heuristic Ratio Estimation (HRE) approach proposes a new way of using the pairwise comparisons matrix. It allows the assumption that the weights of some alternatives (herein referred to as concepts) are known and fixed, hence the weight vector needs to be estimated only for the other unknown values. The main purpose of this paper is to extend the previously proposed iterative HRE algorithm and present all the heuristics that create a generalized approach. Theoretical considerations are accompanied by a few numerical examples demonstrating how the selected heuristics can be used in practice.

20

Heuristic algorithms for the optimization of total weighted completion time for asynchronous transmission in a packet data transmission system

Piórkowski A., Werewka J., Bielecka M.

Control and Cybernetics

|

2014

|

Vol. 43, no. 4

507--529

EN

In this paper, the minimization of total weighted completion time (total cost) for asynchronous transmission in distributed systems is discussed. Special attention has been paid to the problem of message scheduling on the sender side. Messages to be sent form a queue, therefore the order in which they are to be sent has to be set. Scheduling algorithms can be chosen to optimize scheduling criteria such as total completion time or total weighted completion time. The message scheduling problem becomes complicated considerably when the transmitted data stream between the sender and the receiver is formed into packets. TheWSPT (Weighted Shortest Processing Time) scheduling rule, which orders messages according to non-decreasing length and weight ratios has been proven to be non-optimal. It has been demonstrated that the problem of minimizing the total weighted completion time is NP-hard. Here, we propose heuristic algorithms for scheduling messages and experimentally evaluate the performance of these scheduling algorithms.