Many industrial systems involve multiple criteria and objectives, and they are very complex problems in computational science, such as task scheduling. We propose bi-criteria and bi-objective scheduling problems, which are solved by two nature-inspired evolutionary algorithms, such as Simulated Annealing (SA) and Bee Algorithm (BA). This problem is characterized by scheduling a batch of tasks on multiple machines, and it is fundamental because the solution should focus on the simultaneous optimization of two conflicting objectives: the makespan minimization and the total tardiness minimization. This problem is NP-Hard, and therefore, two evolutionary methods were used to search for solutions intelligently in this huge, very complex space. In this research, A mathematical model of the scheduling problem was developed based on the above objectives. Here, we proposed a tailored tune-up of SA and BA, both of which have been specifically developed and implemented to solve the proposed model for integrated scheduling and delivery, geared for the bifunctional nature of the problem. Quantitative results indicate that the Bee Algorithm (BA) achieves a more diverse Pareto front, with an average improvement of approximately 12–18 % in solution diversity compared to Simulated Annealing (SA). In contrast, SA converges faster, reducing computational time by about 30–40 % for large problem instances (n ≥ 80). Overall, BA provides better trade-offs between objectives, while SA offers superior computational efficiency. The results showed that both algorithms can generate solutions that are balanced and time-efficient.
Gas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t
Background: Evaluation and measurement of primary stability could be achieved by several methods, including the resonance frequency analysis (RFA) and implant insertion torque (IT) values. The need for a sufficient primary stability, guaranteed by an adequate insertion torque and implant stability quotient values, increased its importance mainly in one stage implants or in immediate loading protocols. The aims of this study was to find if there is a correlation between the peak insertion torque (PIT) and ISQ values of implants inserted in the jaws of different bone quality which regarded as two important clinical determinant factors for prediction of implant primary stability, and to evaluate and compare whether an experienced clinician cou
... Show MoreValues and ideals are two basic pillars in human life, and high societies have been keen throughout their ages to adhere to and establish them so that man can distinguish good and evil, right and wrong, as they are a balance of actions that give man a higher value. Many of the followers of Abbasid literature, poetry and prose – it is noted that many imams and writers have been keen to highlight these values and make them material for their poetry and literature, courage, generosity, chastity and....All meanings of human values and there is no doubt that one of the texts abounding in this field is what was reported from the people of the house of infallibility pure (peace be upon them), including we touch it in the visit of Imam Jaafar al-
... Show MoreThe pure and Sb doped GeSe thin films have been prepared by thermal flash evaporation technique. Both the structural and optical measurement were carried out for as deposited and annealed films at different annealing temperatures.XRD spectra revealed that the all films have one significant broad amorphous peak except for pure GeSe thin film which annealed at 573 K, it has sharp peak belong to orthorhombic structure nearly at 2θ=33o . The results of the optical studies showed that the optical transition is direct and indirect allowed. The energy gap in general increased with increasing annealing temperature and decreased with increase the ratio of Sb dopant. The optical parameters such as refractive index, extinction coefficient and r
... Show MoreIn this work, The effect of annealing treatment at different temperatures (373, 423 and 473) K and chemical treatment with talwen at different immersion time (40, 60 and 80) min on structural and optical properties of the bulk heterojunction (BHJ) blend copper phthalocyanine tetrasulfonic acid tetrasodium salt/poly dioxyethylenethienylene doped with polystyrenesulphonic acid (CuPcTs/PEDOT:PSS) thin films were investigated. The films were fabricated using spin coating technique. X-ray diffraction (XRD) measurements displayed only one peak at 2θ =4.5o corresponding to (001) direction which has dhkl larger than for standard CuPcTs. The dhkl increase then decrease with increasing annealing temperature and
the time of chemical treatment w
The pure and Sb doped GeSe thin films have been prepared by thermal flash evaporation technique. Both the structural and optical measurement were carried out for as deposited and annealed films at different annealing temperatures.XRD spectra revealed that the all films have one significant broad amorphous peak except for pure GeSe thin film which annealed at 573 K, it has sharp peak belong to orthorhombic structure nearly at 2θ=33o. The results of the optical studies showed that the optical transition is direct and indirect allowed. The energy gap in general increased with increasing annealing temperature and decreased with increase the ratio of Sb dopant. The optical parameters such as refractive index, extinction coefficient and real and
... Show MoreThe convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.
The objective Effect of Internal and External Environment and its Psychological & Practical Reflection on the Political Decision-Making Process
Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh
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