This paper presents an efficient genetic algorithm for solving multiobjective transportation problem, assignment, and transshipment Problems. The proposed approach integrates the merits of both genetic algorithm (GA) ...This paper presents an efficient genetic algorithm for solving multiobjective transportation problem, assignment, and transshipment Problems. The proposed approach integrates the merits of both genetic algorithm (GA) and local search (LS) scheme. The algorithm maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on clustering algorithm. The use clustering algorithm makes the algorithms practical by allowing a decision maker to control the resolution of the Pareto set approximation. To increase GAs’ problem solution power, local search technique is implemented as neighborhood search engine where it intends to explore the less-crowded area in the current archive to possibly obtain more nondominated solutions. The inclusion of local search and clustering algorithm speeds-up the search process and also helps in obtaining a fine-grained value for the objective functions. Finally, we report numerical results in order to establish the actual computational burden of the proposed algorithm and to assess its performances with respect to classical approaches for solving MOTP.展开更多
The goal of efficient computation is to determine reasonable computing cost in polynomial time by using data structure of instance, and analyze the computing cost of satisfactory solution which can meet user’s requir...The goal of efficient computation is to determine reasonable computing cost in polynomial time by using data structure of instance, and analyze the computing cost of satisfactory solution which can meet user’s requirements. When faced with NP-hard problem, we usually assess computational performance in the worst case. Polynomial algorithm cannot handle with NP-hard problem, so we research on NP-hard problem from efficient computation point of view. The work is intended to fill the blank of computational complexity theory.We focus on the cluster structure of instance data of aircraft range problem. By studying the partition and complexity measurement of cluster, we establish a connection between the aircraft range problem and N-vehicle exploration problem, and construct the efficient computation mechanism for aircraft range problem. The last examples show that the effect is significant when we use efficient computation mechanism on aircraft range problem. Decision makers can calculate the computing cost before actually computing.展开更多
文摘This paper presents an efficient genetic algorithm for solving multiobjective transportation problem, assignment, and transshipment Problems. The proposed approach integrates the merits of both genetic algorithm (GA) and local search (LS) scheme. The algorithm maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on clustering algorithm. The use clustering algorithm makes the algorithms practical by allowing a decision maker to control the resolution of the Pareto set approximation. To increase GAs’ problem solution power, local search technique is implemented as neighborhood search engine where it intends to explore the less-crowded area in the current archive to possibly obtain more nondominated solutions. The inclusion of local search and clustering algorithm speeds-up the search process and also helps in obtaining a fine-grained value for the objective functions. Finally, we report numerical results in order to establish the actual computational burden of the proposed algorithm and to assess its performances with respect to classical approaches for solving MOTP.
基金Supported by Key Laboratory of Management,Decision and Information Systems,Chinese Academy of Science
文摘The goal of efficient computation is to determine reasonable computing cost in polynomial time by using data structure of instance, and analyze the computing cost of satisfactory solution which can meet user’s requirements. When faced with NP-hard problem, we usually assess computational performance in the worst case. Polynomial algorithm cannot handle with NP-hard problem, so we research on NP-hard problem from efficient computation point of view. The work is intended to fill the blank of computational complexity theory.We focus on the cluster structure of instance data of aircraft range problem. By studying the partition and complexity measurement of cluster, we establish a connection between the aircraft range problem and N-vehicle exploration problem, and construct the efficient computation mechanism for aircraft range problem. The last examples show that the effect is significant when we use efficient computation mechanism on aircraft range problem. Decision makers can calculate the computing cost before actually computing.
