Improved Squeaky Wheel Optimisation for Driver Scheduling

This paper presents a technique called Improved Squeaky Wheel Optimisation (ISWO) for driver scheduling problems. It improves the original Squeaky Wheel Optimisation’s (SWO) effectiveness and execution speed by incorporating two additional steps of Selection and Mutation which implement evolution within a single solution. In the ISWO, a cycle of Analysis-Selection-Mutation-Prioritization-Construction continues until stopping conditions are reached. The Analysis step first computes the fitness of a current solution to identify troublesome components. The Selection step then discards these troublesome components probabilistically by using the fitness measure, and the Mutation step follows to further discard a small number of components at random. After the above steps, an input solution becomes partial and thus the resulting partial solution needs to be repaired. The repair is carried out by using the Prioritization step to first produce priorities that determine an order by which the following Construction step then schedules the remaining components. Therefore, the optimisation in the ISWO is achieved by solution disruption, iterative improvement and an iterative constructive repair process performed. Encouraging experimental results are reported.

Factors that drive Female Entrepreneurship in Armenia

Entrepreneurs play a key role in any economy. Entrepreneurship includes creativity, innovation, risk taking, planning and management and is described as transferring ideas into action. Female entrepreneurship, in particular, is considered an important tool in enabling female empowerment and emancipation. In the light of recent world events, this has become a crucial area to study and understand, especially with respect to motivations, obstacles, constraints and consequences of female entrepreneurship. Having the previous framework in attention, this thesis focuses on female entrepreneurship in a developing country - Armenia – and proposes a conceptual framework of the phenomenon. A joint cooperation between the World Bank and the European Bank for Reconstruction and Development allowed to conduct an enterprise survey in the country and from that survey a microeconomic dataset was released and applied in this research study. A logistic regression econometric method is applied to the dataset to identify and measure the relationship between female entrepreneurship and several factors such as the location, size, legal status, market and obstacles faced by Armenian firms. The study concludes that women entrepreneurs in Armenia share many common features and obstacles with their male counterparts. Moreover, gender of the top managers, the firm’s location, size, main market type, the number of competitors and full-time employees, the adoption of new marketing methods, the access to land, the tax administration system and an inadequately educated workforce are found to be statistical significant factors in the explanation of female entrepreneurship in Armenia.

An evolutionary squeaky wheel optimisation approach to personnel scheduling

The quest for robust heuristics that are able to solve more than one problem is ongoing. In this paper, we present, discuss and analyse a technique called Evolutionary Squeaky Wheel Optimisation and apply it to two different personnel scheduling problems. Evolutionary Squeaky Wheel Optimisation improves the original Squeaky Wheel Optimisation’s effectiveness and execution speed by incorporating two additional steps (Selection and Mutation) for added evolution. In the Evolutionary Squeaky Wheel Optimisation, a cycle of Analysis-Selection-Mutation-Prioritization-Construction continues until stopping conditions are reached. The aim of the Analysis step is to identify below average solution components by calculating a fitness value for all components. The Selection step then chooses amongst these underperformers and discards some probabilistically based on fitness. The Mutation step further discards a few components at random. Solutions can become incomplete and thus repairs may be required. The repair is carried out by using the Prioritization step to first produce priorities that determine an order by which the following Construction step then schedules the remaining components. Therefore, improvements in the Evolutionary Squeaky Wheel Optimisation is achieved by selective solution disruption mixed with iterative improvement and constructive repair. Strong experimental results are reported on two different domains of personnel scheduling: bus and rail driver scheduling and hospital nurse scheduling.