Fuzzy Modeling for Manpower Scheduling

Fuzzy Modeling for Manpower Scheduling

Michael Mutingi (Namibia University of Science and Technology, Namibia) and Charles Mbohwa (University of Johannesburg, South Africa)
Copyright: © 2014 |Pages: 23
DOI: 10.4018/978-1-4666-4785-5.ch008
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Abstract

Fuzzy theory is an important phenomenon in manpower scheduling, especially in the context where managerial and employee objectives are imprecise and, worst of all, conflicting. In such fuzzy environments, developing robust tools for addressing the fuzzy nature of the problem is imperative. Decision analysts concerned with staff scheduling need robust decision support tools to construct equitable work schedules spanning over a given planning horizon so as to meet organizational objectives, to meet customer requirements, and to satisfy worker preferences. This chapter presents a framework for fuzzy modeling for manpower scheduling based on fuzzy set-theoretic concepts. First, a background on fuzzy modeling approaches is provided, together with their solution methods. Second, key characteristic dimensions of the manpower scheduling problem are identified, leading to a taxonomic framework for classifying manpower scheduling problems. Third, a framework developing fuzzy models for manpower scheduling is derived from the taxonomy, the fuzzy modeling approaches, and the fuzzy solution approaches. The fuzzy models developed can be solved by any appropriate solvers or meta-heuristic methods.
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Introduction

Fuzziness, imprecision, or uncertainties in management objectives and employee preferences are an important area of concern in most organizations, particularly in healthcare institutions (Burke et al. 2004). For instance, fuzzy management goals and objectives, as well as employee preferences, are a common cause for concern when allocating work schedules to employees (Topaloglu and Ozkarahan, 2004). Oftentimes, the management objectives are not expressed precisely but rather in linguistic terms such as “about 8 employees for the morning shift”, or “at most 40 working hours per week”, or “preferably 2 night shifts per week for each employee” and other related vague expressions. Likewise, employee preferences are frequently expressed in natural language terms, such as “preferably 8 working hours per day”, “at least 2 off days”, and other examples. As a result, vagueness of information on management objectives as well as individual preferences leads to uncertainties that need to be addressed when constructing manpower schedules. Under such circumstances, conventional crisp models cannot capture fuzziness inherent in most real-world manpower scheduling problems. In the same vein, Burke et al. (2004) emphasized the need to utilize fuzzy modeling concepts to tackle uncertainties in practical manpower scheduling problems in healthcare institutions. Fuzzy modeling approach is a potential tool in addressing imprecise and conflicting management goals and employee preferences in the area of manpower scheduling.

In a fuzzy environment, manpower scheduling involves construction of effective work schedules spanning over a given planning horizon so as to meet organizational goals, satisfy customer requirements at an acceptable level of service quality, and satisfy worker preferences as much as possible (Ernst et al., 2004b). In this connection, suitable combinations of shifts should be selected from a number of possible shifts, subject to three types of constraints:

  • 1.

    Demand coverage constraints,

  • 2.

    Time related constraints, as well as

  • 3.

    Employee preference constraints (Topaloglu and Ozkarahan, 2004).

Demand coverage constraints refer to the number of workers needed in each period over the course of day, throughout the planning horizon. Time related constraints express the time restrictions on personal schedules such as allowable work duration and shift times. These are influenced by national legislation, union regulations, and workplace regulations. As a result, time constraints tend to be problem specific. Preference constraints refer to the workers’ requests and wishes that should be satisfied as much as possible, if high quality schedules are to be achieved. In most cases, preference constraints usually consider individual staff choices on working time allocation involving daily shift types, work patterns, or days-off assignments.

The practice of manpower scheduling is a complex undertaking that essential seeks to balance individual workloads and satisfy individual preferences leading to high quality schedules, higher worker morale, hence a more effective workforce. However, organizational objectives and individual worker preferences are usually conflicting; workers prefer individualized schedules that consider their preferences while organizations will always try to fulfill demand coverage. Perceived fairness in schedule assignments is an important measure of the quality of work schedules, without which low morale, poor performance, absenteeism and high job turnover are inevitable. Therefore, it is crucial to satisfy workers’ preferences as evenly as possible. On the other hand, the manpower scheduling problem has several possible objectives including

  • 1.

    Minimizing workforce size,

  • 2.

    Maximizing worker preferences

  • 3.

    Minimizing personnel cost,

  • 4.

    Minimizing violation of demand coverage and time-related constraints.

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