Tham khảo tài liệu 'multiprocessor scheduling part 8', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 200 Multiprocessor Scheduling Theory and Applications In this chapter the proposed algorithm is based on the clonal selection principle modeling the fact that only the highest affinity antibodies will proliferate. The distinguishing criterion between antigens and antibodies is Pareto dominance. In other words non-dominated solutions are the antigens and dominated solutions are the antibodies. The multi-objective immune algorithm MOIA implementation is described in the following sections. Fig. 1 presents the pseudo-code of the proposed MOIA. Antibody Representation One of the most important decisions in designing a metaheuristic lies in deciding how to represents solutions and relate them in an efficient way to the searching space. Solution representation must have a one-to-one relation with searching space and besides that should be easy to decode to reduce the cost of the algorithm. Two kinds of different antibody representations are used simultaneously in this study namely job-to-position and continuous representation. Each antibody concurrently has a job-to-position and continuous representation each of them is used in different steps in our algorithm. In the next sections we discuss how and when they are used. Job-to-Position Representation One of the most widely used representations for scheduling problems is job-to-position representation. In this kind of representation a single row array of the size equal to the number of the jobs to be scheduled is considered. The value of the first element of the array shows which job is scheduled first. The second value shows which job is scheduled second and so on. Suppose that the sequence of seven jobs must be determined. Fig. 2 illustrates how this representation is depicted. Location in a sequence 1 2 3 4 5 6 7 Job to be scheduled 1 2 4 3 5 6 7 Figure 2. Job-to-position representation for a flow shop scheduling problem Continuous Representation Tasgetiren et al. 2004 devised a new way of .