Home healthcare worker scheduling : a group genetic algorithm approach

Home healthcare worker scheduling is a hard combinatorial problem concerned with the allocation of care tasks to healthcare givers at a minimal cost while considering healthcare service quality by striving to meet the time window restrictions specified by the patients. This paper proposes a group genetic algorithm (GGA) for addressing the scheduling problem. The approach utilizes the strengths of unique group genetic operators to effectively and efficiently address the group structure of the problem, providing good solutions within reasonable computation times. Computational results obtained show that the GGA approach is effective

Dynamic capacity augmentation strategies for health manpower supply under various demand patterns

Health manpower systems continually face rapidly changing manpower demand due to everchanging health needs all over the globe. Capacity planning for health manpower supply is a strategic issue with increasing complexity and importance. Under dynamic demand patterns characterised by complex dynamic properties, investment in capacity build-up has to be done more cautiously than ever. Otherwise, the necessary human capital growth is retarded or the training system is left with unutilized capacity. This is a great challenge to decision makers when developing manpower supply strategies in turbulent environments. This paper employs the concepts of system dynamics to simulate the impact of different health manpower demand patterns on supply capacity augmentation. Using a typical health manpower system, capacity augmentation policies are simulated against known demand patterns such as steady, ever-growing and fluctuating demand. The simulation model provides an experimental tool, which can be used to evaluate alternative long-term policies based on demand-supply planning reliability as a performance measure. Validation and numerical experimentations further demonstrate the effectiveness of the proposed model, providing sound managerial insights. The approach is useful in designing decision support systems for capacity augmentation in health manpower systems

A home healthcare multi-agent system in a multi-objective environment

Decision making in home care service is complex due to the need to satisfice multi-objective goals such as maximizing customer service quality, minimizing service cost, and maximizing employee satisfaction. With the increasing world-wide need for efficient and effective home healthcare, the increasing elderly population, and the increasing pressure from governments and other stakeholders in various societies, the development of effective novel approaches for home care decisions is imperative. In this paper, we present a multi-agent architecture that facilitates decision making characterised with multiple objectives. The approach integrates the capabilities of a multi-agent system and Web services so as to facilitate effective decisions for home healthcare services. The aim is to provide a multi-agent system based on genetic algorithm, where decisions are based on intelligent agents that provide intelligent alternative decisions in a multiple-objective environment

A group genetic algorithm for the fleet size and mix vehicle routing problem

In logistics management, the use of vehicles to distribute products from suppliers to customers is a major operational activity. Optimizing the routing of vehicles is crucial for providing cost-effective services to customers. This research addresses the fleet size and mix vehicle routing problem (FSMVRP), where the heterogeneous fleet and its size are to be determined. A group genetic algorithm (GGA) approach, with unique genetic operators, is designed and implemented on a number of existing benchmark problems. GGA demonstrates competitive performance in terms of cost and computation time when compared to other heuristics

Task assignment in home health care : a fuzzy group genetic algorithm approach

The assignment of home care tasks to nursing staff is a complex problem for decision makers concerned with optimizing home healthcare operations scheduling and logistics. Motivated by the ever-increasing home-based care needs, the design of high quality task assignments is highly essential for maintaining or improving worker moral, job satisfaction, service efficiency, service quality, and to ensure that business competitiveness remains momentous. To achieve high quality task assignments, the assigned workloads should be balanced or fair among the care givers. Therefore, the desired goal is to balance the workload of care givers while avoiding long distance travels in visiting the patients. However, the desired goal is often subjective as it involves the care givers, the management, and the patients. As such, the goal tends to be imprecise in the real world. This paper develops a fuzzy group genetic algorithm (FGGA) for task assignment in home healthcare services. The FGGA approach uses fuzzy evaluation based on fuzzy set theory. Results from illustrative examples show that the approach is promising

Fuzzy system dynamics simulation for manufacturing supply chain systems with uncertain demand

Real-world manufacturing supply chain systems are characterised by imprecise and dynamic factors. As a result, decision-making takes place in a complex, dynamic and fuzzy environment in which managerial goals and the impacts of possible actions are not precisely known. In a demand driven manufacturing supply chain system, the presence of a fuzzy demand is a serious cause for concern. The present study integrates fuzzy theory and system dynamics simulation to address the fuzzy and dynamic nature of demand-supply factors, from a systems perspective. A set of performance indices were defined to evaluate the system performance. Based on typical demand scenarios, comparative simulation experiments were conducted using the base scenario as a benchmark. The simulation results show the utility of the fuzzy system dynamics approach: (a) the approach represents the real-world picture of a supply chain with fuzzy demand, (b) the supply chain system performs better under dynamic fuzzy policies, and (c) computational “what-if analysis” showed that dynamic fuzzy-based policies are more robust than conventional crisp rules, even in turbulent demand situations. Further managerial insights and practical evaluations are provided in this study

Fuzzy system dynamics and optimization with application to manpower systems

The dynamics of human resource recruitment and training in an uncertain environment creates a challenge for many policy makers in various organisations. In the presence of fuzzy manpower demand and training capacity, many companies fear losing critical human resources when their employees leave. As such, the development of effective dynamic policies for recruitment and training in a fuzzy dynamic environment is imperative

A dynamic simulation of a lean and agile manufacturing system

The integration of just-in-time and lean principles in agile manufacturing plays an important role in enhancing the operational performance of manufacturing systems. In this paper, we address this issue by (i) building a set of performance criteria for a typical manufacturing system, (ii) developing a system dynamics model for the system, and (iii) performing experimental “what-if” simulation analyses. Using a system dynamics simulation methodology, the impact of the application of lean and just-in-time policies on a traditional inventory-focused manufacturing system is investigated. System dynamics modelling is used to capture the dynamic causal linkages between different components of the manufacturing system. Different scenarios are generated in order to investigate the dynamics of the system under assumed demand scenarios. The results of the simulation study reveal that manufacturing systems can benefit from the introduction of lean and just-in-time principles, depending on the extent to which the necessary structural changes are implemented. The paper concludes by providing useful managerial insights for effective implementation of lean and agile manufacturing concepts

Environmental impacts assessment of the platinum nanophase composite electrode by Eco-indicator 99 methodology

Platinum nanophase composite electrode for hydrogen generation by water electrolysis process has to meet sustainable development requirements even in its development phase by reducing GHG emissions to irrelevance. It is therefore important to determine possible emissions, to estimate the energy consumption and identify key parameters in the improvement of the process used to develop the electrode. Eco indicator 99 was used to assess and determine the types of impacts on the environment of the process of the preparation of the composite electrode and Umberto software was used to develop life cycle assessment inventory (LCIA)

Sustainable management in the synfuels sector in South Africa

The debate about the decline in petroleum reserves, the worries over peak oil, the Middle East tension and oil price speculation challenges has made it important to focus on sustainable management and utilization of alternative fuels. The use of alternative fuels to supply the energy needs of the world is not a new concept. This paper reviews coal as a recoverable hydrocarbon-rich resource found in abundant quantities in South Africa (SA). This study review shows that coal will continue to provide a key for the unlocking many of the future global requirements for high-quality energy and chemical building blocks. The historical premise that coal is a dirty fuel is being countered with the continued development and operation of technology to significantly reduce the environmental footprint of coal-sourced energy is investigated. Conclusions are drawn. Firstly, the study brings to our attention that technology is available and is continually being improved to turn coal into synthetic natural gas, transportation fuels, chemicals, chemical intermediates and hydrogen in a way that reduces GHG emissions. Secondly, the study shows that there is a viable coal-to-liquids (CTL) industry in South Africa supplying high-quality middle distillates, in particular diesel fuel, jet kerosene and middle distillate blend stocks. The CTL economics, the potential role of the government and how large-scale development of this industry might impact the environment is analysed on sustainable management