Foraging-directed adaptive linear programming: A hybrid algorithm for discrete/continuous design problems

In this paper, a hybrid, two-stage algorithm, namely, Foraging-directed Adaptive Linear Programming is introduced. The second stage, Adaptive Linear Programming, has been presented in detail elsewhere. Hence, in this paper, the focus is on the first stage which is based on the notion of animals foraging for food in the wild. Two problems are included. In the first, significantly better solutions than previous studies are found and global optimality can be proven. In the second, more complex problem, finding a global optimum is difficult, but various solutions that may not be optimal but are as good or better than previous reports can be found. Therefore, depending upon the complexity of a given problem, the algorithm presented is able to find optimal solutions or identify satisficing solutions or regions where good solutions are located.