In this paper the Discrete Lotsizing and Scheduling Problem (DLSP) is considered. DLSP relates to capacitated lotsizing as well as to job scheduling problems and is concerned with determining a feasible production schedule with minimal total costs in a single-stage manufacturing process. This involves the sequencing and sizing of production lots for a number of different items over a discrete and finite planning horizon. Feasibility of production schedules is subject to production quantities being within bounds set by capacity. A problem classification for DLSP is introduced and results on computational complexity are derived for a number of single and parallel machine problems. Furthermore, efficient algorithms are discussed for solving special single and parallel machine variants of DLSP.
Decision making improves in speed and quality when both the left and right side of our brain is used, i.e. when ratio (using facts) is combined with emotion (using intuition based on learning from experience). However, when learning breaks down, can we still trust our intuition? We analyze information used and decisions made by a new product development team. Our analysis shows that the team did use both rational (news) and emotional (vibes) information. However, good vibes were prioritized over bad news, resulting in decisions of poor quality. Because these decisions seemed good on the short-term, the team failed to realize that the project was in trouble.
Abstract The paper argues that welfare economic principles must be incorporated in post‐disaster humanitarian logistic models to ensure delivery strategies that lead to the greatest good for the greatest number of people. The paper's analyses suggest the use of social costs—the summation of logistic and deprivation costs—as the preferred objective function for post‐disaster humanitarian logistic models. The paper defines deprivation cost as the economic valuation of the human suffering associated with a lack of access to a good or service. The use of deprivation costs is evaluated with a review of the philosophy and the economic literature to identify proper foundations for their estimation; a comparison of different proxy approaches to consider human suffering (e.g., minimization of penalties or weight factors, penalties for late deliveries, equity constraints, unmet demands) and their implications; and an analysis of the impacts of errors in estimation. In its final sections, the paper conducts numerical experiments to illustrate the comparative impacts of using the proxy approaches suggested in the literature, and concludes with a discussion of key findings.
The profitability of remanufacturing depends on the quantity and quality of product returns and on the demand for remanufactured products. The quantity and quality of product returns can be influenced by varying quality-dependent acquisition prices, i.e., by using product acquisition management. Demand can be influenced by varying the selling price. We develop a simple framework for determining the optimal prices and the corresponding profitability. We motivate and illustrate our framework using an application from the cellular telephone industry.
Purpose The European Union (EU) clothing and textile industries are characterized by very intense international competition. EU producers face fierce competition from exports of new industrialized countries whose low wages and social charges give them a considerable competitive advantage. This paper seeks to present the results of an analysis of the European textile sector competitiveness. Design/methodology/approach The analysis is based on an industrial excellence (IE) model developed by INSEAD. This model has been used for the last ten years in an annual award (IEA), given out in France and Germany. This time the model was used not for giving an award, but for assessing and analyzing the current status of industrial excellence in the textile sector. For this reason a sample of textile companies from three European countries was used and results of the analysis are presented. The textile companies that participated in the analysis were benchmarked against the technologically advanced IEA sample consisting of companies from various industries, which participated in the competition during the last three years. Findings Key performance indicators of the textile sector are analyzed, including quality, flexibility, supply chain management, strategy formulation and strategy implementation. Significant improvement potential, especially in the areas of human resource management and knowledge management, is indicated. Research limitations/implications Provides a methodology for employing the IE approach in their operation. Also provides a methodology for analyzing sector performance and new areas of differentiation in the European textile sector. Practical implications The results of the analysis were used to define customized IE training in order to promote expertise in IE in textiles and improve competitiveness of the sector. Originality/value The IEA model is used for the first time, not for giving an award, but as an IE assessment tool which can assist managers both of textile companies and intermediary bodies.
Purpose The purpose of this study is to show that the current complexity of humanitarian operations has only increased the usefulness of system dynamics (SD) in helping decision-makers better understand the challenges they face. Design/methodology/approach A critical analysis to evaluate how SD methodology has been applied to humanitarian operations. Findings Today's humanitarian operations are characterized by huge complexity given the increased number of stakeholders, feedback loops, uncertainty, scarce resources and multiple objectives. The authors argue that SD's tools (causal-loop diagram, data layer, simulation model) have the capacity to appropriately capture this complexity, thereby enhancing intuition and understanding. Originality/value Researchers and practitioners hesitate to use system dynamics when data is missing. The authors suggest alternatives to deal with this common situation.
A firm's raw material sourcing knowledge can be a strategic resource. This article explores how firms can capture and use this knowledge. It examines the sourcing experiences of four firms in four different countries in the automotive industry and identifies the raw material sourcing knowledge-related parameters. Synthesizing the findings from these case studies, it proposes the concept of the sourcing hub—a collaborative center involving the firm, its suppliers, and raw material suppliers—which can effectively capture and deploy the raw material sourcing knowledge for managing value in upstream sourcing.
Field service is gaining importance as after sales service is starting to be recognized as a major source of revenue. This motivates planning problems for companies that employ mobile technicians who provide service on clients' sites. These planning problems share the common characteristic that service levels corresponding to technician response times are explicitly expressed in contracts. Moreover, lately, there is strong pressure from clients to have a single dedicated technician who takes full responsibility of the field service. In this paper, we provide models that enable the analysis of various trade-offs between service levels and operational costs under the dedicated service structure. We also investigate the tradeoffs between strict dedicated service and more flexible structures to understand the settings for which strict dedication is appropriate.
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