This paper discusses the problem of allocation of constrained renewable resource to splittable activities of a single project. If the activities of stochastic projects can be split, these projects may be completed in shorter time when the available resource is constrained. It is assumed that the resource amount required to accomplish each activity is a discrete quantity and deterministic. The activity duration time is assumed to be a discrete random variable with arbitrary experimental distribution. Solving stochastic mathematical programming model of problem is very hard. So, here some existing methods for deterministic problems have been generalized for stochastic case. Solutions of generalized methods are relatively better than random solutions. However, the authors developed the new algorithm that may improve the solutions of generalized methods and project Completion Time Distribution Function (CTDF). Comparison of solution of a method with random solutions is a common assessment method in literature research. Hence, the efficiency of the proposed algorithm represented using this method.

Introduction: Recently, Spirulina platensis has scientifically become popular because of its importance as food, feed, and a natural producer of pigments with specific nutritional and functional characteristics. Materials and Methods: In this study, the effect of various environmental factors affecting growth conditions of Spirulina platensis, including primary inoculation, light-dark cycle, cultivation time, Light-Emitting Diode (LED) composition, nitrogen source, carbon source, and NaCl concentration, on biomass, C-phycocyanin (C-PC), Allophycocyanin (APC) and chlorophyll-a contents were assessed using Placket-Burman Design (PBD). Results: Results showed that out of the seven screened factors, four factors of carbon source, LED composition, light-dark cycle and NaCl concentration significantly affected biomass production (p<0. 01). Among the investigated factors, nitrogen source, light-dark cycle, and NaCl concentration had significant effects on phycocyanin production (p<0. 05). Results showed that cultivation time, light-dark cycle, and NaCl concentration significantly affected the production of allophycocyanin (p<0. 05). Furthermore, NaCl concentration, carbon source, LED composition, cultivation time, and initial inoculation included significant effects on chlorophyll-a production (p<0. 05). Conclusions: The present study screened variables affecting biomass, phycocyanin, allophycocyanin, and chlorophyll-a production as the first step in optimizing Spirulina platensis growth condition. Briefly, NaCl concentration was one of the factors which had a significant impact on all responses. The dark cycle also had an effect on three dependent variables except for chlorophyll-a production.

This paper discusses that the fuzzy metagraphs can be used as a tool for scheduling and control of fuzzy projects. Often, available resources for executing projects may be limited. It is assumed the resources required to accomplish each activity of project (metagraph edges) is renewable. One of the common methods for scheduling projects is using the min-slack. So, first, the forward and backward computations for deterministic metagraphs are described. Then, assuming that the completion time of activities are positive trapezoidal fuzzy numbers, the forward and backward computations are generalized for fuzzy metagraphs. Consequently, completion time of project, earliest and latest time of start and end of activities and floating time of them are obtained as fuzzy numbers. Also, critical activities and critical paths are defined. Then, for scheduling, by using the selected ranking method, the activities of project (metagraph edges) based on min-slack ascending were ordered. Through some numerical examples, calculation steps and the results are illustrated.

In this paper, it is supposed that a project can be shown as a metagraph. The duration of activities are discrete random variables with known probability function, also one kind of consumable and constrained resource is required to execute each activity of the project. Besides, the probability functions of activity durations depend on the amount of the resource allocated to it. Clearly, the amount of resource which can be allocated to each activity is limited to speci c values. In this paper, it is assumed that the due date of project is known and de nite. The objective of this paper is to maximize the probability of completion of stochastic metagraph before the due date of the project. As respects, solving the problem by using the analytical method is very challenging; therefore, we developed a new heuristic method including two sub-algorithms for solving the problem. Twenty examples were designed for examining the proposed algorithm.

Energy consumption has significantly increased beside of urbanization growth. It may go up so fast that it results in environmental Issues and greater natural resource depletions. Therefore, the use of renewable and clean fuel is considered necessary. Currently, macro-algae are cultivated in various regions of the world for various industrial and food usages. Macro-algae are known as a specific resource of alternative for energy production due to their biochemical properties such as high level of carbohydrate, lipid and protein. Various biotechnology methods have been developed for energy producing from macro-algae which are divided into two categories: 1) biochemical processes (fermentation, digestion) and 2) thermochemical processes (incineration, pyrolysis, and hydrothermal liquefaction). Depending on the type of methods, the product are categorized under different phases such as solid, liquid and gas. In this study, we will review the methods and studies on the energy production of different species of macroalgae.

Today, with the growth of the population and increasing trend in the use of electrical energy, the importance of the reliability and stability of the power grid has increased. The ever-increasing development of the power grid and subsequent blackouts of the power grid can lead to serious problems in the daily life and economy of a country. In addition to economic damages, power losses in the power network can lead to dissatisfaction and decreased consumer confidence in the power grid. This research has been carried out to check the application of the genetic algorithm to calculate reliability indices including SAIFI, SAIDI, etc., and its impact on enhancing the reliability of the standard IEEE 33 and 69 bus distribution networks. Additionally, this study explores the GA effectiveness in minimizing both active and reactive power losses. The simulation results in MATLAB, show the constructive effect of applying the GA, shedding light on its potential to optimize the distribution network reliability and minimize power losses, offering valuable insights for power system optimization and reliability improvement.