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ABSTRACTThis paper presents a comparison of two heuristic methods for assigning a part‐time work force to meet varying daily work loads. The authors use actual operating data from Purdue National Bank, Lafayette, Indiana, to make teller staffing decisions. The performance criteria for comparison of the two heuristics is the minimum number of workers employed, minimum number of interbranch transfers, and computer time necessary to attain a solution.

ABSTRACTThis paper examines the use of sampling procedures as a solution methodology for large combinatorial problems. Three sampling strategies are investigated: random sampling (each alternative is equally likely), biased sampling (alternatives' probabilities are biased by specified criteria), and improvement sampling (alternatives' probabilities are dynamically changed based upon new information). These three methodologies are illustrated and compared on the basis of solution quality and computer time requirements.

ABSTRACTThis paper illustrates the use of the Box‐Jenkins methodology by analyzing the Ohio Electrical Power Consumption time series. The three basic analytical steps discussed are the following:1) Model identification ‐ by matching sample autocorrelation functions against theoretical autocorrelation functions.2) Non‐linear estimation of parameters ‐ by minimizing the sum of the squared residuals.3) Diagnostic checking ‐ by analyzing the pattern of the autocorrelation function of the residuals.Regular and adaptive forecasts are then developed using the appropriate model that emerges from the time series analysis.

ABSTRACTThis study revisits the traditional single stage, multi‐item, capacitated lot‐sizing problem (CLSP) with a new integrative focus on problem structuring. Unlike past research, we develop integrative cycle scheduling approaches which simultaneously address lot‐sizing, capacity, and sequencing issues. Our purposes are to (1) explore the effect of sequencing on inventory levels, (2) examine the problem of infeasibility in the economic lot scheduling problem (ELSP), and (3) provide a simple methodology of generating low‐cost cycle schedules in an environment with discrete shipping, dynamic demands, limited capacity, zero setup cost, and sequence‐independent setup times. Our procedures are compared to benchmark cycle scheduling approaches in terms of both inventory cost and computation time under different demand scenarios, using the operating data from a flexible assembly system (FAS) at the Ford Motor Company's Sandusky, Ohio plant.

ABSTRACTThis study focuses on the manpower tour scheduling problem using data from a lockbox system of a commercial bank. The lockbox system uses employees who differ in productivity, hourly cost, number of available working hours per week, and days‐off constraints. These specific problem characteristics require a more general problem formulation and solution procedure for the manpower tour scheduling problem than addressed in previous research. Four heuristic methods for solving the problem (three developed here and a simple round‐up procedure) are tested on a set of forty problems. The results of this study show the effort to develop sophisticated heuristic methods for this class of problems is well justified.

PurposeThe purpose of this paper is to develop a better understanding about drivers of enterprise systems complexity (ESC), as well as its multi‐faceted conceptualization.Design/methodology/approachCase studies were conducted among German Mittelstand companies by an international research team. A grounded theory approach was followed, with the first phase of the case studies being exploratory, and the second phase being more focused.FindingsCase study findings suggest that ESC is a multi‐dimensional construct consisting of the following dimensions: seamlessness, adoption date, number of integrated subsystems, system type/composition, number of functional areas linked, and number of users. Drivers of ESC identified via the case studies include the multi‐dimensional constructs of competition, complexity of processes, complexity of products, global operations, and the firm's customer base. Grounded theory development is used to conceptualize the measures of these drivers. Founded in these exploratory observations propositions for future research are developed.Originality/valueThe research reports on the experiences of companies with enterprise systems (ES), and explores organizational factors determining system complexity; as a sampling frame Mittelstand companies in Southwest Germany are chosen, making this study one of the few exploring ES within this context. The paper also places ESC within theoretical domains, especially the STS theory. The conceptualization of ESC and its antecedents presented provides a starting point for future academic research into this area.