A novel hybrid estimation of distribution algorithm for solving hybrid flowshop scheduling problem with unrelated parallel machine

The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.

Investigation on a vertical radial flow adsorber designed by a novel parallel connection method

Due to the increasing global demand for industrial gas, the development of large-scale cryogenic air separation systems has attracted considerable attention in recent years. Increasing the height of the adsorption bed in a vertical radial flow adsorber used in cryogenic air separation systems may efficiently increase the treatment capacity of the air in the adsorber. However, uniformity of the flow distribution of the air inside the adsorber would be deteriorated using the height-increasing method. In order to reduce the non-uniformity of the flow distribution caused by the excessive height of adsorption bed in a vertical radial flow adsorber, a novel parallel connection method is proposed in the present work. The experimental apparatus is designed and constructed; the Computational Fluid Dynamics(CFD) technique is used to develop a CFD-based model, which is used to analyze the flow distribution, the static pressure drop and the radial velocity in the newly designed adsorber. In addition, the geometric parameters of annular flow channels and the adsorption bed thickness of the upper unit in the parallelconnected vertical radial flow adsorber are optimized, so that the upper and lower adsorption units could be penetrated by air simultaneously. Comparisons are made between the height-increasing method and the parallel connection method with the same adsorber height. It is shown that using the parallel connection method could reduce the difference between the maximum and minimum radial static pressure drop by 86.2% and improve the uniformity by 80% compared with those of using the height-increasing method. The optimal thickness ratio of the upper and lower adsorption units is obtained as 0.966, in which case the upper and lower adsorption units could be penetrated by air simultaneously, so that the adsorbents in adsorption space could be used more efficiently.

Security Constrained Distributed Optimal Power Flow of Interconnected Power Systems

The security constrained distributed optimal power flow （DOPF） of interconnected power systems is presented. The centralized OPF problem of the multi-area power systems is decomposed into independent DOPF subproblems, one for each area. The dynamic security region （DSR） to guarantee the transient stability constraints and static voltage stability region （SVSR） constraints, and line current limits are included as constraints. The solutions to the DOPF subproblems of the different areas are coordinated through a pricing mechanism until they converge to the centralized OPF solution. The nonlinear DOPF subproblem is solved by predictor-corrector interior point method （PClPM）. The IEEE three-area RTS-96 system is worked out in order to demonstrate the effectiveness of the proposed method.

Bi-objective optimization models for mitigating traffic congestion in urban road networks

Traffic congestion in road transportation networks is a persistent problem in major metropolitan cities around the world.In this context,this paper deals with exploiting underutilized road capacities in a network to lower the congestion on overutilized links while simultaneously satisfying the system optimal flow assignment for sustainable transportation.Four congestion mitigation strategies are identified based on deviation and relative deviation of link volume from the corresponding capacity.Consequently,four biobjective mathematical programming optimal flow distribution(OFD)models are proposed.The case study results demonstrate that all the proposed models improve system performance and reduce congestion on high volume links by shifting flows to low volumeto-capacity links compared to UE and SO models.Among the models,the system optimality with minimal sum and maximum absolute relative-deviation models(SO-SAR and SO-MAR)showed superior results for different performance measures.The SO-SAR model yielded 50%and 30%fewer links at higher link utilization factors than UE and SO models,respectively.Also,it showed more than 25%improvement in path travel times compared to UE travel time for about 100 paths and resulted in the least network congestion index of1.04 compared to the other OFD and UE models.Conversely,the SO-MAR model yielded the least total distance and total system travel time,resulting in lower fuel consumption and emissions,thus contributing to sustainability.The proposed models contribute towards efficient transportation infrastructure management and will be of interest to transportation planners and traffic managers.