Resource Investment Problem with Activity Splitting and Resource Window

LU Zhiqiang, ZHOU Haoxue

Abstract

Considering the two characteristics of activity splitting and resource window in the process of aircraft assembly, the model and algorithm of Resource Investment Problem on aircraft mobile production line were studied. Aiming at the situation that some activities have known splitting mode and splitting punishment, an improved genetic algorithm for solving this problem was designed. The traditional real value crossover operation was optimized, and a crossover method based on chromosome fitness value was proposed. Sensitivity analysis was carried out on the range of values of the relevant parameters. A mutation mechanism based on the probability of selection of activity start time was also proposed. For a scheduling scheme that satisfies the optimization conditions, combined with the position of the resource window, after judging whether the splitting activities can be re-scheduled and executed by selecting a new splitting mode and summarizing the different situations, the target resources were further reduced by local operations. The numerical experiments show that, compared with the results of solving the problem of non-split activities with resource window and the basic problem, the average value of the target for the 10, 16, 30, 60, 90 activities is 4.3%. For the comparison between the results of solving this problem and the non-split problem, the average optimization rate is 3.5%, which proves the effectiveness of the algorithm. At the same time, it is proved that the activity splitting is included in the Resource Investment Problem considering the resource window, which can improve the flexibility of problem solving and obtain better scheduling results.

 

 

Keywords: resource investment problem,   resource window,   activity splitting,   genetic algorithm


Full Text:

PDF


References


WANG Y, LU Z Q. Job scheduling optimization of aircraft moving assembly line under multiple constraints [J]. Industrial Engineering and Management, 2011, 16 (6):115-120(. In Chinese)

ZONG B S, LU Z Q. Integrated optimization of project splitting and resource investment project scheduling [J]. Journal of Shanghai Jiaotong University, 2018, 52 (7):793—800.(In Chinese)

MORHING R H. Minimizing costs of resource requirements in project networks subject to a fixed completion time[J]. Operations Research, 1984, 32(1):89—120.

DREXL A, KIMMS A. Optimization guided lower and upper bounds for the resource investment problem[J]. Operational Research Society, 2001, 52 (3):340—351.

DEMEULEMEESTER E L. Minimizing resource availability costs in time -limited project networks [J]. Operations Research and the Management Science, 1995, 41(10):1590—1598.

ZHU X, RUIZ R, LI S Y, et al. An effective heuristic for project scheduling with resource availability cost [J]. European Journal of Operational Research, 2016, 257(3):746—762.

SONG Y, LIU J, WIMMERS M O, et al. A differential evolution algorithm with local search for resource investment project scheduling problems [C]//Evolutionary Computation. Sendai:IEEE, 2015: 1725—1731.

QI J J, LIU Y J, JIANG P, et al. Schedule generation scheme for solving multi -mode resource availability cost problem by modified particle swarm optimization [J]. Journal of Scheduling, 2015, 18 (3):285.

JAVANMARD S, AFSHAR-NADJAFI B, NIAKI S T A. Preemptive multi -skilled resource investment project scheduling problem: Mathematical modelling and solution approaches [J]. Computers & Chemical Engineering, 2017, 96(4):55—68.

REN Y F, LU Z Q. Modeling and optimization of resource investment project scheduling problem with multi -skill [J]. Journal of Tongji University (Natural Science), 2017, 45(11):1713—1721.

JIRACHAI B, DAVID S K. Properties of multi-mode resource-constrained project scheduling problems with resource vacations and activity splitting [J]. European Journal of Operational Research, 2006, 175(1):279—295.

QI F Z, HU D, YE L H. Study on resource allocation of multi-project based on time window and critical chain[J]. Science and Technology Management Research, 2013, 33 (13):229—232. (In Chinese)

LU Z Q, SHI T. Modeling and optimization of resource investment problem with activity splitting[J]. Computer Integrated Manufacturing System, 2018, 24(3):602—611. (In Chinese)

CHEN X P, YU S L. Improvement on crossover strategy of real-valued genetic algorithm [J]. Acta Electronica Sinica, 2003, 31(1): 71—74 (In Chinese)


Refbacks

  • There are currently no refbacks.