Partner selection for reverse logistics centres in green supply chains: a fuzzy artificial immune optimisation approach

The design of reverse logistics networks has now emerged as a major issue for manufacturers, not only in developed countries where legislation and societal pressures are strong, but also in developing countries where the adoption of reverse logistics practices may offer a competitive advantage. This paper presents a new model for partner selection for reverse logistic centres in green supply chains. The model offers three advantages. Firstly, it enables economic, environment and social factors to be considered simultaneously. Secondly, by integrating fuzzy set theory and artificial immune optimisation technology, it enables both quantitative and qualitative criteria to be considered simultaneously throughout the whole decision-making process. Thirdly, it extends the flat criteria structure for partner selection evaluation for reverse logistics centres to the more suitable hierarchy structure. The applicability of the model is demonstrated by means of an empirical application based on data from a Chinese electronic equipment and instruments manufacturing company.     

Line balance analyses for system assembly lines in an electronic plant

This research analysed and optimised the assembly line balance of notebook computer system production lines in a major computer plant. The research developed a mathematical model for balancing assembly lines of a specific notebook computer system. Precedence relationship charts were created to enforce the required sequences and ILOG CPLEX software was used to obtain the optimal solution of the task assignments to the workstations. The new task assignments were simulated to verify the improvement recommendations and predict the potential benefits.The estimated improvements include: (1) 5.9% increase in average daily production; (2) 29% decrease in average daily WIP; (3) 67.9% reduction in cycle time; (4) 16.7% reduction in operator headcount over the whole system assembly area. The contributions of this research include: (1) Establishing line balancing mathematical model suitable for notebook computer factories; (2) Optimising the system assembly lines for the subject company; (3) Transferring the line balance modelling and optimisation techniques for company use.     

Determination of anaerobic threshold

This report describes the estimation of the parameters for a model of ventilation (y) by human subjects as a two-segment linear function of oxygen uptake (x). Experimental data were supplied by R.L. Hughson of the Department of Kinesiology. The analysis of one of nine available sets of data is described in detail.     

Multilocation plant sizing and timing problem: a study of spatial—temporal decomposition procedure

An attempt has been made to develop a spatial-temporal decomposition procedure to solve the multilocation plant sizing and timing problem (MLPSTP). MLPSTP involves the determination of site, location, timing and utilization of the plants to meet the demands of geographically distributed customers. These decisions are assumed to interact through a common objective of minimizing the net present value (NPV) of capital costs and streams of operating and transportation costs. A solution procedure for MLPSTP is proposed using aggregation and disaggregation methodology. In the aggregation phase, MLPSTP is considered to be a single-period problem. This problem is decomposed over different geographical areas to obtain a set of feasible sites and projects. These projects are then sequenced over a finite planning horizon in the disaggregation phase. A multiple criteria based evaluation of spatial decomposition, temporal decomposition, and spatial-temporal decomposition is provided.     

OPTIMIRUS. Simulating Population Change in the Russian Far East

This article examines the population trends in the cities of the Russian Far East between the two census years 1989 and 2002. Three geographical models – Rank-Size Rule, Temperature per Capita and a simple gravity model – are used to describe the direction of these population trends. An economic efficiency function is constructed from the three models to simulate an ideal population distribution for the Russian Far East. The heart of the simulation is a conjugate gradient optimisation of the economic efficiency function. The results serve as an important backdrop to discussions of current population trends and serve as an important backdrop to discussions of current population trends and as basis for recommendations concerning future changes in the spatial distribution of population in the region.Mueller, K., et Bradshaw M. J., 2006. OPTIMIRUS. Une simulation des variations de population dans l’Extrême-Orient russe. Revue européenne de démographie, 22:105–126.     

Development and implementation of an operating room scheduling tool: an action research study

In this study, we report the results of an action research project whose aim was to develop and implement an operating room scheduler at the Meyer University Children’s Hospital. The study offers insights into the features that make an MSS optimisation model and scheduler effective and easy to implement, and shed light on those actions facilitating their introduction and use. Specifically, it suggests that creating an effective operating room scheduler requires clustering patients in homogeneous surgery groups and developing a flexible tool that allows: scheduling surgery groups instead of actual patients, easily adding/removing constraints, changing the objective function(s) and adjusting the planning horizon. In addition, it posits that gaining the commitment of top management by showing credible preliminary results, inferring stakeholder preferences by letting them comment on tentative schedules, introducing changes gradually and involving staff at lower levels of the hospital hierarchy can significantly facilitate the scheduler development and implementation.     

Decision process of allocating projects to project managers

Allocating projects to project managers (PM) is a crucial decision in project management. Choosing the PM must be undertaken in a structured way, and thereby take into account the needs of the project and the PM’s competences and availability. The proposed model optimises the total time that PMs have available and takes into account the constraint of the switchover time loss within the mathematical programming. It model is part of a three-stage approach where: (1) projects are sorted using a multicriteria approach; (2) PMs are sorted using a multicriteria approach; and (3) the final allocation to intra-classes of projects is made using the optimisation model. This proposal contributes to aiding decision-makers involved in allocating projects: by respecting the limit of the time that PMs have available, or by extrapolating PMs’ available hours in which case overtime will have to be used. The model is applied in a Brazilian Energy Company.     

Towards a socio-oecotechnology

The paper will attempt to demonstrate that within the broad ambit of the socio-technical model there is scope for development and for a degree of innovation. Two aspects of the model will be progressed and to some extent integrated. Firstly, I will argue that the joint optimisation (JtO) concept has not been elaborated and emphasised as much as it deserves and it needs to be sharply differentiated from the widely used notion of maximisation. Secondly, using JtO, I will extend the two system socio-technical model to a troika model by including the impact of technology on the oecological environment.¹ To obtain the best overall results, JtO has to be achieved between three systems: the social, the technical and the oecological. In this way, the extended model will engage with the public’s rapidly growing awareness of environmental hazards for which it frequently blames technologies. This extension also raises the socio-technical model from the micro- to the meso- and macro-level which was always the intention of the early pioneers. These theoretical developments will be treated heuristically and briefly illustrated by two case examples from recent research.     

EF-based strategies for productivity improvements at wet-etch stations

Abstract

In complex manufacturing environments, Cycle Time (CT) reductions obtained at critical production steps could generate considerable productivity improvements and lead to capacity increases at no investment costs. A wet-etch station operating in a real semiconductor manufacturing plant has been modelled to investigate the impact of different assignment strategies on CT performance. Assignment strategies based on the “Earliest Finish” (EF) concept have been developed and their productivity efficiency compared with a workload balance-based strategy. The EF-based strategies differ from each other for both computational complexity and amount of real-time information required. Encouraging results obtained for a high detail level EF strategy have inspired the development of conceptually similar strategies characterised by reduced implementation efforts. Fundamental implementation constraints, suggested by the manufacturing engineers familiar with the wet-etch station, have been taken into account throughout the different stages of this study. CT reductions ranging between 11% and 28% could be achieved at the modelled wet-etch station.