An algorithm for single shift scheduling of hierarchical workforce

Narasimhan, Rangarajan

doi:10.1016/s0377-2217(96)00364-5

Cited by 35 publications

(13 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For examples of recent research, see Morris and Showalter (1983), Easton and Rossin (1991), Bechtold et al (1991), Ryan (1992), Brusco andJohns (1995, 1996), Lau (1996), Narasimhan (1996), Langerman and Ehlers (1997), Caprara et al (1997), Beaumont (1997), Brusco (1998), Alfares (1998), Higgins (1998), Teodorović and Lučić (1998), Aykin (2000), Yan and Tu (2002), Yan et al (2004Yan et al ( , 2006aYan et al ( , 2006bYan et al ( , 2008aYan et al ( , 2008b. Of these, Yan et al (2008b) developed several deterministic models for mass rapid transit carriage maintenance manpower supply plans, which is more closely related to our research.…”

mentioning

confidence: 99%

Short-term manpower planning for MRT carriage maintenance under mixed deterministic and stochastic demands

2010

View full text Add to dashboard Cite

The purpose of this research is to develop two manpower supply planning models and a solution algorithm for mass rapid transit carriage maintenance under mixed deterministic and stochastic demands. These models are formulated as mixed integer programs that are characterized as NP-hard. We employ problem decomposition techniques, coupled with the CPLEX mathematical programming solver, to develop an algorithm that is capable of efficiently solving the problems. The models and the method used currently in actual operations are evaluated by a simulation-based evaluation method. Finally, we perform a case study using real operating data from a Taiwan MRT maintenance facility. The preliminary results are good, showing that the models could be useful for planning carriage maintenance manpower supply.

show abstract

mentioning

confidence: 99%

Short-term manpower planning for MRT carriage maintenance under mixed deterministic and stochastic demands

2010

View full text Add to dashboard Cite

show abstract

“…To our knowledge Emmons and Burns [23] were the first to develop efficient algorithms for the "days-off-scheduling problem" with hierarchical personnel categories. More recently, integer programming and genetic algorithm based solution approaches have been developed to deal with heterogeneous workforce [24][25][26][27]. However, less attention has been paid to personnel assignment problems, which are of crucial importance in almost all manufacturing and service systems.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Constraints (26) ensure that the staffing requirements of each study are satisfied. Employees must not be assigned to conflicting, i.e.…”

Section: Objective Functionmentioning

confidence: 99%

Development of a Decision Support Model for Scheduling Clinical Studies and Assigning Medical Personnel

Grunow

Günther

Yang

2004

Health Care Manage Sci

View full text Add to dashboard Cite

Clinical studies for the development of new drugs in the pharmaceutical industry consist of a number of individual tasks which have to be carried out in a pre-defined chronological order. Each task requires certain types of medical personnel. This paper investigates the scheduling of clinical studies to be performed during a short-term planning horizon, the allocation of workforce between the studies, and the assignment of individual employees to tasks. Instead of developing a complex monolithic decision model, a hierarchical modelling approach is suggested. In the first stage, a compact integer optimization model is solved in order to determine the start-off times of the studies and the required staffing while taking the limited availability of personnel into account. The objective is to minimize total staffing costs. The assignment of individual employees to tasks is then made in the second stage of the procedure using a binary optimization model.

show abstract

“…In the same line of research [20] discussed necessary and sufficient condition for a labor mix to be feasible and presented one-pass method that gives the least labor cost. Reference [21] developed a mathematical model that solves the problem by determining the most economical size of various hierarchies of workers, assigning them working and off days in each week. Reference [22] illustrated that integer programming approach is well suited for solving the problem studied by Ref.…”

Section: Introductionmentioning

confidence: 99%

Production Planning for Make-to-Order Flow Shop System Under Hierarchical Workforce Environment

Piya

Al-Hinai

2015

Transactions on Engineering Technologies

View full text Add to dashboard Cite

In make-to-order system orders are scheduled for production based on the due date agreed with customer and the strategy of company. Production planning of such system includes scheduling of orders to the production periods and allocation of workers at different work centers. Complexity in the system arises when the operation to perform next and its processing time is skilled dependent where a higher qualified worker type can substitute a lower qualified one, but not vice-versa. Under such working environment, efficient scheduling of orders and allocation of workers at different work center play major role to improve system performance. This paper develops a mathematical model for make-to-order flow shop system under hierarchical workforce environment. The model helps identify optimum schedule of orders and allocation of workers with an objective of minimizing the weighted average earliness and tardiness. A heuristic method is also proposed to overcome the complexity of mathematical model and solve the problem efficiently. Numerical analysis indicates that proposed heuristic is capable of finding optimal or near optimal solution in a considerably reduced amount of computational timing.

show abstract

An algorithm for single shift scheduling of hierarchical workforce

Cited by 35 publications

References 8 publications

Short-term manpower planning for MRT carriage maintenance under mixed deterministic and stochastic demands

Short-term manpower planning for MRT carriage maintenance under mixed deterministic and stochastic demands

Development of a Decision Support Model for Scheduling Clinical Studies and Assigning Medical Personnel

Production Planning for Make-to-Order Flow Shop System Under Hierarchical Workforce Environment

Contact Info

Product

Resources

About