A priority based unbalanced time minimization assignment problem

OPSEARCH ◽  
2019 ◽  
Vol 57 (1) ◽  
pp. 13-45
Author(s):  
Ekta Jain ◽  
Kalpana Dahiya ◽  
Vanita Verma
OPSEARCH ◽  
2020 ◽  
Author(s):  
Prabhjot Kaur ◽  
Kalpana Dahiya ◽  
Vanita Verma

2016 ◽  
Vol 40 (17-18) ◽  
pp. 7784-7795 ◽  
Author(s):  
Prabhjot Kaur ◽  
Anuj Sharma ◽  
Vanita Verma ◽  
Kalpana Dahiya

2018 ◽  
Vol 28 (2) ◽  
pp. 219-235
Author(s):  
Bindu Kaushal ◽  
Shalini Arora

This paper discusses a priority based time minimizing transporation problem in which destinations are prioritized so that the material is supplied, based upon the priorities of the destinations. All the destinations, which are at priority, are served first in Stage-I while the demands of the secondary destinations are met in Stage-II. It is assumed that secondary transportation can not take place until the primary transportation is done. The purpose is to transport in such a manner that the sum of the transportation time of primary and secondary destinations is minimum. To achieve this, two approaches are proposed. In the first approach, primary destinations are served optimally by giving weights while in the second approach, lexicographic optimization is used. From the generated pairs, the minimum sum of times corressponding to Stage-I and Stage-II times is picked up as the optimal solution. It is also shown, through Computational Details, that the lexicographic optimization converges to the optimal solution faster than the first approach as reported in Table 4.


2018 ◽  
Vol 37 (2) ◽  
pp. 713-736
Author(s):  
Ekta Jain ◽  
Kalpana Dahiya ◽  
Anuj Sharma ◽  
Vanita Verma

Risks ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 25
Author(s):  
Helena Gaspars-Wieloch

The assignment problem (AP) is a discrete and combinatorial problem where agents are assigned to perform tasks for efficiency maximization or cost (time) minimization. AP is a part of human resource project management (HRPM). The AP optimization model, with deterministic parameters describing agent–task performance, can be easily solved, but it is characteristic of standard, well-known projects realized in a quiet environment. When considering new (innovation or innovative) projects or projects performed in very turbulent times, the parameter estimation becomes more complex (in extreme cases, even the use of the probability calculus is not recommended). Therefore, we suggest an algorithm combining binary programming with scenario planning and applying the optimism coefficient, which describes the manager’s nature (attitude towards risk). The procedure is designed for one-shot decisions (i.e., for situations where the selected alternative is performed only once) and pure strategies (the execution of a weighted combination of several decision variants is not possible).


2009 ◽  
Vol 42 (18) ◽  
pp. 10-11
Author(s):  
ROBERT H. HOPKINS

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