As the knowledge-based economy society comes, knowledge workers, which has replaced capital, facilities, raw m...
WANG Yifan 1 , CHEN Di 1,2 , LIU Shixin 1 ,ZENG Qingfu 3 1. College of Information Science & Engineering, Northeastern University, Shenyang 110819, China2. Department of Information Technology and Business Administration, Dalian Neusoft Institute of Information, Dalian 116023, China3. Shandong Iron and Steel Group Logistics Center, Jinan 250132, China
The steelmaking process scheduling problem by considering variable electricity price (SMSPVEP) was investigated. A decomposition approach was proposed for the SMSPVEP. At the first stage, mathematical programming was utilized to minimize the maximum completion time for each cast without considering variable electricity price. At the second stage, based on obtained relative schedules of all casts, a mathematical model was formulated with an objective of minimizing the energy cost for all casts scheduling problem. The two-stage models were tested on randomly generated instances based on the practical process in a Chinese steelmaking plant. Computational results demonstrate the effectiveness of the proposed approach.
A memetic algorithm(MA) for a multi-mode resourceconstrained project scheduling problem(MRCPSP) is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called "strategic oscillation" to make the search process have a higher probability to visit solutions around a "feasible boundary". One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.
