Bioinspired Computation and Its Applications in Operation Management

Bioinspired computation is an umbrella term for different computational technologies that are based on principles or models of biological systems. This class of approaches, including evolutionary algorithm, swarm intelligence, and artificial immune system, complements traditional ones in the sense that the former can be applied to large and complex combination optimization problems, but the latter encounters difficulties. Therefore, bioinspired technologies are becoming important in the face of solving discrete and dynamic problems. Recently, the bioinspired computation has attracted much attention of researchers and has also been widely applied to operation management fields ranging between production assembling, inventory control, project scheduling, human resource management, and revenue management. However, due to complexity and uncertainty in operation management problems, it is very difficult to find out the optimum solution under the limited resources, time, and money in real-world applications using the bioinspired technologies. Therefore, it is necessary to develop efficient or improved algorithms to solve operation management problems. The main objective of this special issue is to present the original research and review articles on the latest theoretical and practical achievements that will contribute to the field of bioinspired computation and its applications in operation management, in all branches of management science and computer science. The special issue received 66 high-quality submissions from different countries all over the world. All submitted manuscripts have followed the same standard (peer-reviewed by at least three independent reviewers) as applied to regular ones to " this journal. " Due to space limit, only 24 papers could be published (acceptance ratio of 1 : 3). Inevitably, difficult decisions had to be made, and some high-quality submissions could not be included. The primary guideline was to demonstrate the wide scope of bioinspired computation and applications in operation management. Besides, some novel research questions from different applications that are worth further investigation in the future are also included. In the paper, " A hybrid genetic-simulated annealing algorithm for the location-inventory-routing problem considering returns under e-supply chain environment, " Y. Li et al. formulate a location-inventory-routing problem model with no quality defects' returns. In addition, to solve this NP-hard problem, an effective hybrid genetic-simulated anneal-ing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA in computing time, optimal solution, and computing stability. Moreover, the proposed model is also very useful in helping managers make the right decisions under e-supply chain environment. In the paper " Optimization and …