On Manpower Scheduling Algorithms

Tien, James M.; Kamiyama, Angelica

doi:10.1137/1024063

Cited by 128 publications

(45 citation statements)

References 23 publications

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“…Tien and Kamiyama [15] proposed three main stages to solve a scheduling problem, once the predictions of load are known. First step, named allocation, computes the number of agents needed for each period of the planning.…”

Section: Previous Workmentioning

confidence: 99%

Tabu Search to Plan Schedules in a Multiskill Customer Contact Center

Mendes¹,

Lucet²,

Moukrim

2006

2006 International Conference on Service Systems and Service Management

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We have studied a realistic case of scheduling problem in a customer contact center, dealing with multiskill agents. Our model combines the last two steps of the standard approach by determining shifts and by assigning them to agents at the same time (scheduling and rostering). Moreover, we have considered realistic vacations, according to legal constraints and preferences of agents. We have envisioned entire weeks of work, with variable meal times and meal durations, without overtime. In this paper, we define the problem and describe a Tabu search based solution.

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Section: Previous Workmentioning

confidence: 99%

Tabu Search to Plan Schedules in a Multiskill Customer Contact Center

Mendes¹,

Lucet²,

Moukrim

2006

2006 International Conference on Service Systems and Service Management

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“…The typical process of planning and scheduling a workforce in an organization is inherently a multiphase activity (Tien and Kamiyama, 1982). First, the production or the personnel management have to determine the temporal staff requirements, i.e., the number of employees needed for each timeslot of the planning period.…”

Section: Introductionmentioning

confidence: 99%

The minimum shift design problem

Gaspero

Gärtner²,

Kortsarz

et al. 2007

Ann Oper Res

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The min-SHIFT DESIGN problem (ÅË ) is an important scheduling problem that needs to be solved in many industrial contexts. The issue is to find a minimum number of shifts and the number of employees to be assigned to these shifts in order to minimize the deviation from workforce requirements.Our research considers both theoretical and practical aspects of the min-SHIFT DESIGN problem. This problem is closely related to the minimum edge-cost flow problem (Å ), a network flow variant that has many applications beyond shift scheduling. We show that ÅË reduces to a special case of Å and, exploiting this reduction, we prove a logarithmic hardness of approximation lower bound for ÅË . On the basis of these results, we propose a hybrid heuristic for the problem which relies on a greedy heuristic with a min-cost max-flow subroutine based on the network flow analogy followed by a local search algorithm that makes use of multiple neighborhood relations. An experimental analysis on structured random instances shows that the hybrid heuristic clearly outperforms our previous commercial implementation and highlights the respective merits of the composing heuristics for different performance parameters.

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“…Most of these problems are extremely difficult and have been regarded as being more complex than the travelling salesman problem (Tien and Kamiyama, 1982). Early research (e.g.…”

Section: Introductionmentioning

confidence: 99%

An Estimation of Distribution Algorithm with Intelligent Local Search for Rule-based Nurse Rostering

Aickelin

Burke

2007

SSRN Journal

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Abstract-This paper proposes a new memetic evolutionary algorithm to achieve explicit learning in rule-based nurse rostering, which involves applying a set of heuristic rules for each nurse's assignment. The main framework of the algorithm is an estimation of distribution algorithm, in which an ant-miner methodology improves the individual solutions produced in each generation. Unlike our previous work (where learning is implicit), the learning in the memetic estimation of distribution algorithm is explicit, i.e. we are able to identify building blocks directly. The overall approach learns by building a probabilistic model, i.e. an estimation of the probability distribution of individual nurse-rule pairs that are used to construct schedules. The local search processor (i.e. the ant-miner) reinforces nurse-rule pairs that receive higher rewards. A challenging real world nurse rostering problem is used as the test problem. Computational results show that the proposed approach outperforms most existing approaches. It is suggested that the learning methodologies suggested in this paper may be applied to other scheduling problems where schedules are built systematically according to specific rules.

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On Manpower Scheduling Algorithms

Cited by 128 publications

References 23 publications

Tabu Search to Plan Schedules in a Multiskill Customer Contact Center

Tabu Search to Plan Schedules in a Multiskill Customer Contact Center

The minimum shift design problem

An Estimation of Distribution Algorithm with Intelligent Local Search for Rule-based Nurse Rostering

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