Bi-objective project portfolio selection and staff assignment under uncertainty

被引:40
|
作者
Gutjahr, Walter J. [1 ]
Reiter, Peter [1 ]
机构
[1] Univ Vienna, Dept Stat & Decis Support Syst, A-1010 Vienna, Austria
基金
奥地利科学基金会;
关键词
project portfolio selection; staff scheduling; stochastic optimization; multi-objective optimization; PERFORMANCE ASSESSMENT; ALLOCATION; ALGORITHM; OPTIMIZERS; MODEL;
D O I
10.1080/02331931003700699
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
We formulate a project portfolio selection problem under uncertainty with two optimization criteria: a weighted average of economic and strategic gains, and a risk measure expressed as the expected total overtime cost. The optimal assignment of personnel with given skills to the tasks of the selected projects is incorporated as a subproblem. Searching for Pareto-optimal portfolios satisfying the given constraints amounts to a stochastic multi-objective combinatorial optimization problem, a problem type for which only a few general solution approaches are available at present. We apply a recently developed technique called adaptive Pareto sampling, solve a linear subproblem with an LP solver and use the NSGA-II algorithm for deterministic multi-objective optimization as an auxiliary procedure. A convergence result applicable in a more general context is also shown. To obtain objective function estimates, importance sampling is applied. The technique is tested on a benchmark derived from a real-world application case provided by the E-Commerce Competence Center Austria.
引用
收藏
页码:417 / 445
页数:29
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