An optimal semi-online algorithm for 2-machine scheduling with an availability constraint

This paper considers a problem of semi-online scheduling jobs on two identical parallel machines with objective to minimize the makespan. We assume there is an unavailable period [B,F] on one machine and the largest job processing time P _max? is known in advance. After comparing B with P _max? we consider three cases, and we show a lower bound of the problem are 3/2, 4/3 and \((\sqrt{5}+1)/2\), respectively. We further present an optimal algorithm and prove its competitive ratio reaches the lower bound.     

Risk assessment based on a STPA–FMEA method: A case study of a sweeping robot

Despite rapid developments in the quality and safety of consumer products, the rise of intelligent household appliances, such as sweeping robots, has introduced new safety concerns. Considering “person–product–environment” elements and the complex systems of emerging consumer products, this study presents a new method of risk assessment for consumer products: systems theoretic process analysis (STPA)–failure mode and effects analysis (FMEA). As a case study, this method is applied to the safety control of a sweeping robot. The results suggest that this method can identify all the possible failure modes and injury scenarios among the product components, and the safety constraints in the hierarchical control structure of the interactive system. Moreover, the STPA–FMEA method combines user and environmental factors with the value of product risk events, based on the risk priority number (RPN). This provides an accurate and orderly system to reduce or eliminate the root causes of accidents and injuries. Finally, analysis of unsafe control behavior and its causes can be used to suggest improved safety constraints, which can effectively reduce the risk of some injury scenarios. This paper presents a new method of risk assessment for consumer products and a general five-level complex index system.     

Environmental and economic assessment for the optimal configuration of a sustainable solid waste collection system: a ‘kerbside’ case study

The article presents a case study concerning the improvement of the ‘kerbside’ waste collection system, now increasingly implemented in many Italian municipalities, as an alternative to traditional bring collection, with the aim of increasing the quality of waste collection and the collection rate, in order to reduce the final impact on the environment. A planning model for an integrated waste management system based on kerbside collection is presented. A heuristic procedure is also applied in order to obtain some admissible solutions of the real problem in reasonable computational time. The economic and environmental impacts are considered as significant elements for the evaluation and validation of the obtained solutions. Five alternative configurations of kerbside system, diverging in number of sub-area, synchrony of vehicles and directionality of the arcs, are compared in an economic point of view. Finally, Life-Cycle Assessment is used as a tool to compare the overall potential environmental impacts of the alternative of kerbside collection systems and also to compare the kerbside system with the traditional bring one. The different scenarios of kerbside system are comparable in terms of damage on the impact categories, while the bring system is the worst one, in terms of damage on human health, in the consumption of resources and also for the total damage score.     

A note on ‘a strategy for optimal equipment replacement’

A recent article in this journal outlined strategies for the replacement of components and sub-assemblies when considering hazard rates and for capital intensive equipment when considering influences such as increasing maintenance costs, inflation, discount rates, and depreciation. We expand upon this second analysis, concerning the replacement of capital intensive equipment with net present value (NPV) analysis, by guaranteeing that all feasible options are evaluated when determining the optimal strategy. This requires assumptions about future challengers (potential replacement equipment over time) and the time horizon for analysis. We illustrate different solution approaches based on the given assumptions.     

An improvement on “Integrated production strategy and reuse scenario: A CoFAQ model and case study of mail server system development”

The authors (Tang et al. (2013) [1] developed a CoFAQ model to formulate a solution for the problem of production strategy decision and reuse scenario selection for a software product family. In the previous research, we stated that the CoFAQ model was a 0–1 mixed integer nonlinear program, where only a local optimal solution might be found. In a recent study, we found that the CoFAQ could be transformed into a 0–1 mixed integer linear programming model. By solving the model, a global optimal solution can be obtained. In this paper, we present the improved formulation and the optimal solution for the case study.     

Data mining driven DMAIC framework for improving foundry quality – a case study

Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) methodology has been widely used across industries as the best systematic and data driven problem solving approach for quality improvement. Statistical Design of Experiment (DOE) is used in the ‘Improve’ stage for obtaining optimal process settings for significant variables contributing towards quality improvement. But, DOE is an offline activity requiring time and other resources for conducting experiments and analyses. Further, there are many small and medium scale enterprises that cannot afford to conduct DOE. Under such practical constraints, it is desirable to apply DMAIC using online process data under day-to-day production situations or with little changes in process settings without compromising production. In this article, we propose a DMAIC framework, driven by data mining techniques for defect diagnosis and quality improvement where historical and online process data can be effectively utilised. We have used two decision tree algorithms namely, Classification and Regression Tree and Chi-squared Automatic Interaction Detection in developing the proposed framework. The proposed approach is applied in an Indian grey iron foundry where conducting DOE is not a feasible option for the management. The result demonstrates a significant reduction in casting defect and validates the practical viability of this approach.     

International collaborative ventures between higher education institutions: a British–Russian case study

The starting point for our research is a model of developmental space designed by Coenders. Developmental space in this model is a social space arising from interaction between people. Coenders states that this developmental space is conditional for the probability of success for groups working on innovation. This model is relevant and useful because it is increasingly common for groups in organizations to work on innovation. Human Resource Development (HRD) professionals, involved in organizational development, often facilitate these groups as a process consultant. The model of Coenders is not complete yet, and for analysing and influencing the developmental space, the model is too complex. In a developmental research, we refine and adjust the model of the developmental space. The goal of our study is to develop a model of the developmental space as a starting point for groups and HRD professionals to analyse and influence that space.     

Districting for parcel delivery services – A two-Stage solution approach and a real-World case study

This paper studies a real-world problem arising in the context of parcel delivery. Given a heterogeneous set of resources, i.e., different drivers and different vehicles, the problem for each day consists of assigning a driver and a vehicle to each customer requiring service. Two conflicting aspects must be taken into account. On the one hand, service consistency is desirable, meaning that a customer should always be served by the same driver. On the other hand, daily demand fluctuations and tight resource constraints prohibit fixed resource assignments. With the aim of finding a reasonable compromise between these aspects, we propose a novel two-stage districting approach, which establishes delivery districts in the first stage and adapts them to the daily demand realizations in the second stage. For the first stage problem we propose three models that differ in the level of detail of their input data, their expected compliance with service consistency and the driver’s contractual working times, and their computational effort. Our two-stage approach merges the two dominant approaches in the literature, which either determine a priori routes and then adapt them on a daily basis, or derive fixed service regions for drivers. We present a case study based on a real-world data set. The results highlight the differences between the three first stage models and show that only few adaptations of the districts are necessary in the second stage to achieve feasible daily delivery tours along with a very good workload balance for drivers. We also analyze the effects of a homogeneous vs a heterogeneous fleet, of full time drivers vs full and part time drivers, and of the location of the depot and the length of the planning horizon.     

An empirical study of design and testing of hybrid evolutionary–neural approach for classification

We propose a hybrid evolutionary–neural approach for binary classification that incorporates a special training data over-fitting minimizing selection procedure for improving the prediction accuracy on holdout sample. Our approach integrates parallel global search capability of genetic algorithms (GAs) and local gradient-descent search of the back-propagation algorithm. Using a set of simulated and real life data sets, we illustrate that the proposed hybrid approach fares well, both in training and holdout samples, when compared to the traditional back-propagation artificial neural network (ANN) and a genetic algorithm-based artificial neural network (GA-ANN).     

An extension of the relaxation algorithm for solving a special case of capacitated arc routing problems

In this paper, we propose an exact method for solving a special integer program associated with the classical capacitated arc routing problems (CARPs) called split demand arc routing problems (SDARP). This method is developed in the context of monotropic programming theory and bases a promising foundation for developing specialized algorithms in order to solve general integer programming problems. In particular, the proposed algorithm generalizes the relaxation algorithm developed by Tseng and Bertsekas (Math. Oper. Res. 12(4):569–596, 1987) for solving linear programming problems. This method can also be viewed as an alternative for the subgradient method for solving Lagrangian relaxed problems. Computational experiments show its high potential in terms of efficiency and goodness of solutions on standard test problems.     

Is advertising for losers? An empirical study from a value creation and value capturing perspective

Does advertising lead to higher profits? This question has preoccupied company executives and academic researchers for many decades. Arguments have been put forth in both directions, and evidence is mixed at best. In this article, we re-examine the question from a value creation and value capturing perspective, which allows us to re-interpret and reconcile the different views and empirically validate the resulting hypotheses. Using a database of the top 500 brands of established companies during the 2008–2015 period, we find that advertising spending has no significant impact on profitability, while both brand value and research and development (R&D) spending have a clearly positive effect. In addition, we observe a positive interaction effect between advertising spending and R&D spending and a negative interaction between brand value and R&D spending on profitability. These findings corroborate the view that advertising in and of itself does not improve profitability; rather, its effect is positive only when it acts in support of customer value creation as a result of R&D.     

Are skilled contingent workers neglected? Evidence from a cross-sector multiple case study on organizational career management practices

The study aims to discover the extent to which organizations support the careers of skilled contingent workers (SCWs) by providing them with organizational career management (OCM) practices. Analyzing three Belgian companies from different sectors, we find that SCWs do benefit from OCM practices. Such practices cover three dimensions: formalization, individual focus, and differentiation. Subsequently, we explain the three dimensions, respectively, through three contextual variables: the legal and regulatory framework, companies’ human resource management (HRM) configurations and the value of human capital, and the roles of third-party actors. The association of the variables with such dimensions enables the development of three research propositions. This study paves the way for additional research on SCWs and their careers as well as incorporating this population in HRM strategies, including that of OCM practices.     

REDUTEX: a hybrid push–pull production system approach for reliable delivery time in knitting SMEs

The textile sector is composed of small and medium enterprises (SMEs) worldwide. Nowadays there is a shortage of technological knowledge in SMEs. Lead time is a critical indicator in any productive company organisation. The aim of this research was to provide an approach, called REDUTEX, based on theoretical concepts of lean and synchronous manufacturing in order to help to understand the behaviour of SMEs and to improve the manufacturing process by reducing the customer lead times. The integration of these philosophies is the basis of REDUTEX; a hybrid push–pull production system approach to knitting SMEs. With this approach, it is possible to obtain a process reliability when the restrictive resource capacity (RRC) is identified, optimised and protected. By synchronising all activities to the rhythm of RRC, through a continuous flow, it is possible to obtain high-impact results through a dual automated system and product quality, through a visual control. REDUTEX uses a push system from the RRC to the location of the supermarket, where accumulated inventory may be distributed in the internal assembly department and external family workshops, making a pull system. Subsequent re-assembly processes use a push system until the end of the product. The stages of REDUTEX are explicitly described and applied to real data, so that the staff of SMEs can easily understand the behaviour of the process and implement it. One of the advantages of REDUTEX is that it does not need highly trained staff. The research methodology was conducted as a case of study in twelve SMEs and validated and implemented in three textile companies of the southern area of the state of Guanajuato in Mexico, obtaining reliable delivery times and very promising results.     

Note on: An integrated vendor–buyer cooperative inventory model for items with imperfect quality

Huang [Huang, C., 2002. An integrated vendor–buyer cooperative inventory model for items with imperfect quality. Production Planning and Control, 13 (4), 355–361] proposes an integrated inventory model which allows a vendor and a buyer to minimise their expected integrated total cost function when the vendor's production process is not perfect. This note identifies two errors in the paper and provides a reformulation of the model.     

Toward a comprehensive perspective on hubristic leadership – An aggregation of cross-disciplinary evidence and roadmap for future research

A growing body of literature reveals that the emergence of hubris is by no means a rare phenomenon in leadership contexts. Despite having been repeatedly proven that hubris has both beneficial and detrimental manifestations in leadership behaviors, its positioning as a harmful cognitive bias continues to echo across disciplines. To unify the fragmented hubris tradition, this paper synthesizes existing literature and identifies three perspectives on hubristic leadership: an innovation perspective, an internal coordination and commercialization perspective, and a risk management perspective. The aggregation of these perspectives into a unifying theoretical framework indicates that the type of leadership behavior together with the predictability of its outcomes account for the ambivalent manifestations of hubris across leadership behaviors. Future research opportunities are discussed on this basis.