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It is the complexity and the calculated quantities which require the use of the general algorithm for evaluating the maximum flow of the network. The logical cutting tree algorithm model of the network maximum flow is built using both the logical thought of the fault tree method and cutting set theories of the graphics. Therefore, the problem is resolved well and its calculation process is simpler and its logic is better than the original algorithm method.

Maximum-flow of an uncertain multi-owner network has become very important recently. This study aims to evaluate the maximum flow on a cooperated logistic system in the presence of uncertainties, raised by travel time, capacity, cost and failures.

To consider different uncertainties and to promote network efficiency, the proposed model is enriched with a cooperative game methodology and a reliability method. A scenario-based method covers optimistic, pessimistic and most likely estimates time, cost and capacity of each route as well as applies a prior failure pattern for breakdown of any resource.

A linear optimization model, which is enriched with target reliability estimation, is presented. Results on a water distribution network indicate more revenue performance for players. Carrying out sensitivity analysis shows the importance of the model parameters.

Modeling maximum-flow problem in the presence of many sources of uncertainty with the aim of a cooperative game is the main contribution of the present study. Also, a novel method based on the reliability theory is applied to close the chasm on evaluating the real maximum flow in a shared decentralized network which suffers from risky conditions on arcs and nodes.

The European Union (EU) energy supply environment is changing significantly and in a dynamic way, establishing the issue of safe energy imports as main priority. Greece relies heavily on energy imports. Furthermore, Greece aims to be elevated into an energy cross road for the energy supply to the EU. In this respect, the aim of this paper is the investigation of the suitability of graph theory concepts on energy supply networks and its application to represent energy corridors to Greece.

Supporting frameworks to represent and assess the vulnerability of the corridors satisfying the Greek demand in oil and gas are considered a crucial issue and are presented in this paper, based on the graph theory approach. In addition, a pilot application of the shortest path algorithm and the maximum flow at minimum risk algorithm for the oil and gas corridors to Greece is presented and discussed.

This paper introduces the application of graph theory to energy policy analysis. Indeed, the pilot application in oil and gas supply corridors to Greece, although quite simplified, has indicated the applicability of graph theory concepts in such problems and is considered a step forward of the existing studies, supporting the design efforts towards the development of a more reliable energy supply system.

To the best of the authors' knowledge, graph theory's application to energy corridors is not available in the international literature. In this respect, the added value of the paper is the provision of a sufficient decision support framework for the representation and assessment of the energy corridors' risk of energy availability, through the application of graph theory.

Cellular and functional layouts were investigated under a variety of real‐world conditions via a two‐stage computer simulation study. In the first stage, simulation models were developed for three actual companies. Six different cell formation procedures were used to develop the cellular layouts and CRAFT was used to develop the functional layout. The following six variables were used to measure shop performance: average flow time, maximum flow time, average distance travelled by a batch, average work‐in‐process level, the maximum level of work‐in‐process, and the longest average queue. Factors observed in the first stage of the study that appear to make cellular manufacturing less beneficial than might otherwise be expected were found to be small batch sizes, a small number of different machines the parts require in their processing, short processing times per part, the existence of bottleneck machines (i.e. machines with insufficient capacity), and the absence of natural part families (i.e. sets of parts with similar processing requirements). In the second stage of this study, earlier assumptions associated with sequence‐dependent setup times and move time delays were relaxed. These two parameters were identified as important factors as well.

In response to the station design and flexible resources allocation of the aircraft moving assembly line, a new problem named flexible resource investment problem based on project splitting (FRIP_PS), which minimizes total cost of resources with a given deadline are proposed in this paper.

First, a corresponding mathematical model considering project splitting is constructed, which needs to be simultaneously determined together with job scheduling to acquire the optimized project scheduling scheme and resource configurations. Then, an integrated nested optimization algorithm including project splitting policy and job scheduling policy is designed in this paper. In the first stage of the algorithm, a heuristic algorithm designed to get the project splitting scheme and then in the second stage a genetic algorithm with local prospective scheduling strategy is adopted to solve the flexible resource investment problem.

The heuristic algorithm of project splitting gets better project splitting results through the job shift selection strategy and meanwhile guides the algorithm of the second stage. Furthermore, the genetic algorithm solves resources allocation and job schedule through evaluation rules which can effectively solve the delayed execution of jobs because of improper allocation of flexible resources.

This paper represents a new extension of the resource investment problem based on aircraft moving assembly line. An effective integrated nested optimization algorithm is proposed to specify station splitting scheme, job scheduling scheme and resources allocation in the assembly lines, which is significant for practical engineering applications.

The purpose of this study is to use the incompressible smoothed particle hydrodynamics method to examine the influences of a magnetic field on the double-diffusive convection caused by a rotating circular cylinder with paddles within a square cavity filled by a nanofluid.

The cavity is saturated by two wavy layers of non-Darcy porous media with a variable amplitude parameter. The embedded circular cylinder with paddles carrying T_h and C_h is rotating around the cavity center by a uniform circular velocity.

The lineaments of nanofluid velocity and convective flow, as well as the mean of Nusselt and Sherwood numbers, are represented below the variations on the frequency parameter, amplitude parameter of the wavy porous layers, Darcy parameter, nanoparticles parameter, Hartmann number and Ryleigh number. The performed simulations showed the role of paddles mounted on circular cylinders for enhancing the transmission of heat and mass within a cavity. The wavy porous layers at the lower Darcy parameter are playing as a blockage for the nanofluid flow within the porous area. Increasing the concentration of the nanoparticles to 6% reduces the maximum flow speed by 8.97% and maximum streamlines |ψ|_max by 10.76%. Increasing Hartmann number to 100 reduces the maximum flow speed by 65.83% and |ψ|_max by 75.54%.

The novelty of this work is to examine the effects of an inclined magnetic field and rotating novel shape of a circular cylinder with paddles on the transmission of heat/mass in the interior of a nanofluid-filled cavity saturated by undulating porous medium layers.

Road pricing is an efficient strategy for managing urban traffic to relieve congestion. The macroscopic fundamental diagram (MFD), which relates the average network density and flow, is a simple tool for assessing road pricing effects on transportation network performance. However, recent research indicates that it may have complexity (an MFD hysteresis loop), especially for city-scale networks. Although ignoring MFD hysteresis may provide inaccurate results, pricing models that consider this hysteresis are scarce. This paper aims to assess road pricing effects on network performance considering MFD hysteresis characteristics.

This paper evaluated different pricing strategies spatially and temporally and compared network performance based on MFD shape in the presence of MFD hysteresis loops. These strategies were developed on a multimodal (cars and buses) network using a multi-agent transport simulation (MATSim).

This study found that pricing some links for a short duration with an optimum charge calculated based on the MFD provides higher travel time savings than the previous relevant studies.

These findings may facilitate assessing road pricing effects on multimodal network performance considering MFD hysteresis.

The aim of this study is to report the effect of different content of calcium oxide on the process of electromelting magnesia.

The process of molten magnesia was analyzed by finite element simulation and proved by scanning electron microscope.

The results show that with the increase of CaO content, the maximum temperature appreciation increases from 3,616°C To 3,729°C, showing an approximate nonlinear evolution. Low thermal conductivity and low specific heat of CaO result in higher temperature. With the increase of CaO content and temperature, the maximum flow velocity of MgO slag increases from 0.043 to 1.34 mm/s. Under different initial CaO contents, the distribution trend of CaO volume fraction is basically the same, and the CaO volume fraction is evenly distributed between 50 and 225 mm in the furnace.

The influence of different contents of impurity calcium oxide on the process of electromelting magnesia was analyzed and a theoretical system was established.