An Integer Programming Model for the Ferry Scheduling Problem

Author(s):  
Daniel Karapetyan ◽  
Abraham P. Punnen
2010 ◽  
Vol 5 (1) ◽  
pp. 54-62 ◽  
Author(s):  
Rafael Pastor ◽  
Albert Corominas

PurposeThe purpose of this paper is to propose a bicriteria integer programming model for hierarchical workforce scheduling in which the first criterion is the cost and the second is the suitability of task assignment to individual employees. The model is based on the integer programming formulation for the hierarchical workforce scheduling problem published in 2007 by Seçkiner et al., which extends the model proposed by Billionnet in 1999.Design/methodology/approachThe principal hypothesis of this paper is that, although an employee is capable of performing several different tasks with equal efficiency, the type of task to which he/she is assigned affects the overall suitability of the assignment configuration. Therefore, cost‐minimising solutions should also optimise task assignment when possible. This paper considers real cases and confirm that this approach to the problem is appropriate for dealing with common situations in personnel management.FindingsThe proposed idea is applied to the example problem used by Seçkiner et al. and the results are compared with Seçkiner et al.'s model results.Originality/valueConsequently, the proposal is more general and a more faithful representation of the problems faced by personnel managers, which should help to bridge the gap between academic studies and practical cases.


2010 ◽  
Vol 156-157 ◽  
pp. 633-637
Author(s):  
Xiao Le Han ◽  
Zhi Qiang Lu ◽  
Li Feng Xi

In this paper the multiprocessor task scheduling problem with variable job profile is addressed. Such problem originates from many practical resource assignment contexts. Based on discretized parameters, the problem is formulated as an integer programming model. Due to the complexity of the problem, a Lagrangian relaxation is applied to solve the problem. The numerical experiment demonstrates the effectiveness of our algorithm procedure.


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