Bilinear Assignment Problem: Large Neighborhoods and Experimental Analysis of Algorithms

The bilinear assignment problem (BAP) is a generalization of the well-known quadratic assignment problem. In this paper, we study the problem from the computational analysis point of view. Several classes of neighborhood structures are introduced for the problem along with some theoretical analysis. These neighborhoods are then explored within a local search and variable neighborhood search frameworks with multistart to generate robust heuristic algorithms. In addition, we present several very fast construction heuristics. Our systematic experimental analysis disclosed some interesting properties of the BAP, different from those of comparable models. We have also introduced benchmark test instances that can be used for future experiments on exact and heuristic algorithms for the problem.

SCHEDULING OF CONSTRUCTION PROJECTS WITH APPLICATION OF METAHEURISTIC ALGORITHMS

The paper presents the authors’ research on the application of metaheuristic algorithms in Time Coupling Methods (TCM). The experimental analysis of algorithms: tabu search, genetic search, simulated annealing and B&B algorithm was conducted in the paper. The application of these algorithms, which are currently used to solve job scheduling problems, allows one to obtain better suboptimal solutions than with the currently used B&B algorithm. The main branch of the authors’ research is developing the methodology of construction works scheduling with the application of TCM 17,8,9 1013. The problems of scheduling linear construction works using time-cost optimisation are worked out.