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In the practical production, the transportation of jobs is existed between different machines. These transportation operations directly affect the production cycle and the production efficiency. In this study, an improved memetic algorithm is proposed to solve the flexible job shop scheduling problem with transportation times, and the optimization objective is minimizing the makespan. In the improved memetic algorithm, an effective simulated annealing algorithm is adopted in the local search process, which combines the elite library and mutation operation. All the feasible solutions are divided into general solutions and local optimal solutions according to the elite library. The general solutions are executed by the simulated annealing algorithm to improve the quality, and the local optimal solutions are executed by the mutation operation to increase the diversity of the solution set. Comparison experiments with the improved genetic algorithm show that the improved memetic algorithm has better search performance and stability.

<abstract> <p>The flexible job shop scheduling problem is important in many research fields such as production management and combinatorial optimization, and it contains sub-problems of machine assignment and operation sequencing. In this paper, we study a many-objective FJSP (MaOFJSP) with multiple time constraints on setup time, transportation time and delivery time, with the objective of minimizing the maximum completion time, the total workload, the workload of critical machine and penalties of earliness/tardiness. Based on the given problem, an improved ant colony optimization is proposed to solve the problem. A distributed coding approach is proposed by the problem features. Three initialization methods are proposed to improve the quality and diversity of the initial solutions. The front end of the algorithm is designed to iteratively update the machine assignment to search for different neighborhoods. Then the improved ant colony optimization is used for local search of the neighborhood. For the searched scheduling set the entropy weight method and non-dominated sorting are used for filtering. Then mutation and closeness operations are proposed to improve the diversity of the solutions. The algorithm was evaluated through experiments based on 28 benchmark instances. The experimental results show that the algorithm can effectively solve the MaOFJSP problem.</p> </abstract>

Sulfate polysaccharides, such as heparin sulfate, have been found to have inhibitory activity against SARS-CoV-2. An abalone polysaccharide, AGSP, was deeply sulfate modified using the chlorosulfonic acid/pyridine method, yielding S-AGSP. AGSP and S-AGSP inhibitions of SARS-CoV-2 infection of Vero E6 cells were tested in vitro. The interference of AGSP or S-AGSP on the binding interaction between the SARS-CoV-2 spike protein and angiotensin-converting enzyme was tested using a biolayer interferometry assay. Results showed that S-AGSP, above a concentration of 1.87 µg/mL, significantly inhibited SARS-CoV-2 infection of Vero E6 cells. Compared with AGSP, S-AGSP obviously weakened the affinity between the SARS-CoV-2 spike protein and ACE2. The polysaccharide’s sulfate content played a vital role in influencing the binding affinity of spike protein to ACE2. Therefore, S-AGSP has potential as a COVID-19 competitive inhibitor as well as a candidate to be repurposed as a prophylactic COVID-19 therapeutic.