A goal programming-based approach for multi-period security services scheduling

Abstract

A shift system implementation is usually required in scheduling security services which also causes important managerial challenges due to the necessity of the 7 days-24 hours continuous nature of the corresponding services. In the construction of a shift schedule, it is also necessary to consider some criteria about the humanitarian issues, such as the equality of not only the number workdays but also the number ofshifts for each person as well as the ones imposed by the corresponding labor law legislation usually about the maximum number of workdays and shift transitions. Construction of an ideal schedule for security services under the aforementioned constraints is thus a challenging task, especially for the large-sized real-life problems due to the increases in both the number of people and the length of the planning horizon. An idea to deal with the curse of dimensionality in the shift-scheduling problem is dividing a planning horizon into shorter periods, which might reduce problem size significantly; however, it also requires a flexible approach for relating the solutions of the consecutive periods. Such a flexible approach for relating the corresponding schedules of the consecutive periods is proposed in this study where we propose an integer-goal programming formulation that efficiently handles the issue. Purpose: In this study, we aim at proposing a flexible approach to solve large-scale shift scheduling problems bydividing the planning horizon into shorter periods for problem size reduction. Theory and Methods: We propose a goal programming-based approach for multi-period security services scheduling (Figure A). Results: We illustrate the performance of the proposed approach on a real-life problem involving the construction ofthe monthly schedules in a year for a security team of a hundred people. Conclusion: It is noted from the computational experiments that the proposed formulation is able to construct the corresponding monthly schedules in a few minutes, implying its potential for use real-life shift scheduling problems.