Research on optimal decision-making of cloud manufacturing service provider based on grey correlation analysis and TOPSIS

It is of great practical significance to optimise the decision-making of cloud manufacturing service providers, which can ensure the efficient operation of the cloud manufacturing services. In order to effectively optimise, this paper constructs the evaluation index system, sorts out 7 important evaluation indexes. A method is proposed on the basis of the TOPSIS method and Grey Correlation Analysis (GRA), which is a decision-making method combining static distance and dynamic trend, and make the evaluation results more reasonable. In addition, in order to reflect the true weight of the high dimensional index, the evaluation model of projection pursuit index is established. The improved Particle Swarm Optimisation (PSO) algorithm is used to optimise the projection index function and model parameters, and to obtain the objective weights of evaluation indexes. Then the objective weights combine with the subjective weights obtained by the Analytic hierarchy process (AHP), which makes the weights of the evaluation indexes achieve the unity of subjective and objective. Finally, 20 sets of simulation examples are given to illustrate the feasibility and effectiveness of the proposed method.     

Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations

Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO₂ emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.     

Development and optimisation of a defined high cell density yeast medium

Saccharomyces cerevisiae cells grown in a small volume of chemically defined media neither reach the desired cell density nor grow at a fast enough rate to scale down the volume and increase the sample number of classical biochemical assays, as the detection limit of the readout often requires a high number of cells as an input. To ameliorate this problem, we developed and optimised a new high cell density (HCD) medium for S. cerevisiae. Starting from a widely used synthetic medium composition, we systematically varied the concentrations of all components without the addition of other compounds. We used response surface methodology to develop and optimise the five components of the medium: glucose, yeast nitrogen base, amino acids, monosodium glutamate, and inositol. We monitored growth, cell number, and cell size to ensure that the optimisation was towards a greater density of cells rather than just towards an increase in biomass (i.e., larger cells). Cells grown in the final medium, HCD, exhibit growth more similar to the complex medium yeast extract peptone dextrose (YPD) than to the synthetic defined (SD) medium. Whereas the final cell density of HCD prior to the diauxic shift is increased compared with YPD and SD about threefold and tenfold, respectively. We found normal cell-cycle behaviour throughout the growth phases by monitoring DNA content and protein expression using fluorescent reporters. We also ensured that HCD media could be used with a variety of strains and that they allow selection for all common yeast auxotrophic markers.     

Structural analysis and optimization of a tethered swept wing for airborne wind energy generation

In this paper, we present an aero‐structural model of a tethered swept wing for airborne wind energy generation. The carbon composite wing has neither fuselage nor actuated aerodynamic control surfaces and is controlled entirely from the ground using three separate tethers. The computational model is efficient enough to be used for weight optimisation at the initial design stage. The main load‐bearing wing component is a nontypical “D”‐shaped wing‐box, which is represented as a slender carbon composite shell and further idealised as a stack of two‐dimensional cross section models arranged along an anisotropic one‐dimensional beam model. This reduced 2+1D finite element model is then combined with a nonlinear vortex step method that determines the aerodynamic load. A bridle model is utilised to calculate the individual forces as a function of the aerodynamic load in the bridle lines that connect the main tether to the wing. The entire computational model is used to explore the influence of the bride on the D‐box structure. Considering a reference D‐box design along with a reference aerodynamic load case, the structural response is analysed for typical bridle configurations. Subsequently, an optimisation of the internal geometry and laminate fibre orientations is carried out using the structural computation models, for a fixed aerodynamic and bridle configuration. Aiming at a minimal weight of the wing structure, we find that for the typical load case of the system, an overall weight savings of approximately 20% can be achieved compared with the initial reference design.     

A fast branch,bound and remember algorithm for disassembly line balancing problem

In recent years, the interests of disassembly line have increased owing to economic reasons and the increase of environmental awareness. Effective line can provide many advantages in terms of economic aspect and it facilitates competition the companies with others. This study contributes to the relevant literature by a branch, bound and remember algorithm for disassembly line balancing problem with AND/OR precedence. The proposed exact solution method employs the memory-based dominance rule to eliminate the reduplicated sub-problems by storing all the searched sub-problems and to utilise cyclic best-first search strategy to obtain high-quality complete solutions fast. In this paper, minimising the number of stations is taken as the performance measure. The proposed methodology is tested on a set of 260 instances and compared with the mathematical model using CPLEX solver and five well-known metaheuristics. Computational results show that the proposed method is capable of obtaining the optimal solutions for all the tested instances with less than 0.1?seconds on average. Additionally, comparative study demonstrates that the proposed method is the state-of-the-art algorithm and outperforms the CPLEX solver and metaheuristics in terms of both solution quality and search speed aspects.     

Robust optimum design of tuned liquid column damper in seismic vibration control of structures under uncertain bounded system parameters

The optimum design of a tuned liquid column damper (TLCD) considering system parameter uncertainty is usually performed by minimising the performance measure obtained by the total probability theory without any consideration to the variation of its performance due to parameter uncertainty. However, such a design method does not necessarily correspond to an optimum design in terms of maximum response reduction as well as its minimum dispersion. Furthermore, such approach cannot be applied in many real situations when the required detailed information about the uncertain parameters is limited. The robust design optimisation (RDO) of a TLCD system to mitigate seismic vibration effect in which the bounds on the magnitude of the uncertain properties of the structural and ground motion model parameters are only required is attempted in this study. The RDO is formulated as a two-criterion optimisation problem where the weighted sum of the maximum root mean square displacement of the structure and its dispersion is minimised. The conventional interval analysis-based bounded optimum solution is also obtained to demonstrate the effectiveness of the proposed RDO approach. A numerical study elucidates the effect of parameter uncertainty on the RDO of TLCD parameters by comparing the RDO results with the bounded optimum results.     

Conceptual framework for decentralized green water‐infrastructure systems

We present a model for a decentralized green water‐infrastructure system (DGWIS) based on a new conceptual framework that optimises the use of captured rainwater, recycled wastewater and renewable energy resources. DGWIS is designed for building‐scale localised water supply systems that utilise rainwater and greywater and incorporate advanced small‐scale water treatment systems and renewable local energy sources such as solar and wind. Several constraints are considered: (i) available renewable energy; (ii) greywater production rate; (iii) potential captured rainwater; (iv) water demand; (v) water storage volumes required to accommodate greywater, harvested rainwater and separate water/energy supplies from the city and (vi) water treatment capacities. The proposed DGWIS optimisation framework demonstrates proof‐of‐concept and provides a solid foundation for an innovative paradigm shift towards water and energy sustainability.     

Hybrid approach for congestion management using optimal placement of distributed generator

Congestion management (CM) in a large power system network is a difficult task which can be solved by placing one or more distributed generators (DGs) on congested lines. The first concern is to determine the exact location of congested line for the placement of optimal size of DG so that cost can be minimised. In this work, hybridisation of firefly technique and differential evolution optimisation search has been proposed, which manages congestion effectively by rescheduling of generators satisfying the system constraints both technically and economically in the deregulated market scenario. To validate the proposed hybrid approach, results have been compared with firefly optimisation technique results. It is observed that the hybrid approach is an efficient tool in handling CM resulting in a secure operation to reduce flows in the heavily loaded lines with low system loss and increasing power capability with improved stability of network by controlling power flows in the network.     

Concurrent multi-scale modelling and updating of long-span bridges using a multi-objective optimisation technique

This paper aims at developing an innovative technique of concurrent multi-objective optimisation for updating the multi-scale model of long-span bridges. A multi-scale model is established for the purpose of concurrently analysing the global response of the structure and nonlinear local damages in order to assess structural state and local damage evolution or deteriorating, respectively. A multi-objective optimisation technique is proposed in this work for concurrent multi-scale model updating, in which several key issues including the determination of the objective functions and constraint conditions, the multi-objective optimisation algorithm and how to find the optimal solution from many non-inferior solutions are studied. The proposed concurrent multi-objective optimisation technique is applied to update the initial multi-scale model of Runyang Suspension Bridge (RYSB) near Shanghai, and the updated model is validated by the data from the field tests conducted for obtaining the response in global (dynamic properties) and local levels.     

Optimal design of stepped spillways using the HBMO algorithm

Studies on stepped spillways as flood energy dissipators have been conducted to understand the hydraulics on the stepped face of roller-compacted concrete dams as well as overlays of embankment dams. Significant energy losses occur along the stepped chute so that the energy dissipation structure becomes smaller and more economic. In addition, considering the design discharge, downstream face slope, height of spillway, different combinations of spillway width and number of spillway steps may lead to different head losses. In each feasible combination, the remaining head after the steps should be dissipated by downstream energy dissipators. Design and construction of spillways and energy disspators are very cost-consuming and build up a major part of the dam's construction expenses. Thus, the cost of a financially viable stepped spillway project that consists of the steps’ cost and downstream dissipator's cost should be minimised. In this paper, the honey-bee mating optimisation (HBMO) algorithm is used to determine the best combination of design variables so as to minimise the total cost of both spillway chute and stilling basin. Results are compared with those previously obtained by genetic algorithm (GA) and show the promising potential of the HBMO algorithm in this field of application.