Minimization of total energy consumption in an m-machine flow shop with an exponential time-dependent learning effect  

作　　者：Lingxuan LIU Zhongshun SHI Leyuan SHI 

机构地区：[1]Department of Industrial Engineering & Management,Peking University [2]Department of Industrial & Systems Engineering,University of Wisconsin-Madison

出　　处：《Frontiers of Engineering Management》2018年第4期487-498,共12页工程管理前沿（英文版）

摘　　要：This study investigates an energy-aware flow shop scheduling problem with a time-dependent learning effect. The relationship between the traditional and the proposed scheduling problem is shown and objective is to determine a job sequence in which the total energy consumption is minimized. To provide an efficient solution framework, composite lower bounds are proposed to be used in a solution approach with the name of Boundsbased Nested Partition(BBNP). A worst-case analysis on shortest process time heuristic is conducted for theoretical measurement. Computational experiments are performed on randomly generated test instances to evaluate the proposed algorithms. Results show that BBNP has better performance than conventional heuristics and provides considerable computational advantage.This study investigates an energy-aware flow shop scheduling problem with a time-dependent learning effect. The relationship between the traditional and the proposed scheduling problem is shown and objective is to determine a job sequence in which the total energy consumption is minimized. To provide an efficient solution framework, composite lower bounds are proposed to be used in a solution approach with the name of Boundsbased Nested Partition(BBNP). A worst-case analysis on shortest process time heuristic is conducted for theoretical measurement. Computational experiments are performed on randomly generated test instances to evaluate the proposed algorithms. Results show that BBNP has better performance than conventional heuristics and provides considerable computational advantage.

关 键 词：flow SHOP ENERGY-AWARE scheduling learning effect nested PARTITION worst-case error bound 

分 类 号：N[自然科学总论]