A Comparison of Operator Utility Measures for On-Line Operator Selection in Local Search

This paper investigates the adaptive selection of operators in the context of Local Search. The utility of each operator is computed from the solution quality and distance of the candidate solution from the search trajectory. A number of utility measures based on the Pareto dominance relationship and the relative distances between the operators are proposed and evaluated on QAP instances using an implied or static target balance between exploitation and exploration. A refined algorithm with an adaptive target balance is then examined

Using Local Search with adaptive operator selection to solve the Progressive Party Problem

This paper investigates the use of adaptive operator selection in the context of Local Search to solve a constraint satisfaction problem, namely the Progressive Party Problem. Operators are selected according to a utility value which is computed, for each operator, from the solution quality and from the distance of the candidate solution to recently visited solutions in the search trajectory. We show that using several non-problem-specific operators gives comparable successful resolution rates to an algorithm customized for the problem, albeit with slower run times

An Exploration-exploitation Compromise-based Adaptive Operator Selection for Local Search

This paper deals with the adaptive selection of operators in the context of local search (LS). In evolutionary algorithms, diversity is a key concept. We consider a related idea: the similarity between the candidate solution and the solutions in the search trajectory. This notion, together with the solution quality, is used to evaluate the performance of each operator. A new utility measure for LS operators, evaluating relative distances between the operators, is introduced. It is compared with an existing measure based on the Pareto dominance relationship using some basic selection schemes. An adaptive version of the algorithm is also examined. The proposed methods are tested on the Quadratic Assignment Problem and Asymmetric Traveling Salesman Problem

A Hybrid Metaheuristic Approach to a Real World Employee Scheduling Problem

Employee scheduling problems are of critical importance to large businesses. These problems are hard to solve due to large numbers of conflicting constraints. While many approaches address a subset of these constraints, there is no single approach for simultaneously addressing all of them. We hybridise 'Evolutionary Ruin & Stochastic Recreate' and 'Variable Neighbourhood Search' metaheuristics to solve a real world instance of the employee scheduling problem to near optimality. We compare this with Simulated Annealing, exploring the algorithm configuration space using the irace software package to ensure fair comparison. The hybrid algorithm generates schedules that reduce unmet demand by over 28% compared to the baseline. All data used, where possible, is either directly from the real world engineer scheduling operation of around 25,000 employees , or synthesised from a related distribution where data is unavailable

The Local Optima Level in Chemotherapy Schedule Optimisation

In this paper a multi-drug Chemotherapy Schedule Optimisation Problem (CSOP) is subject to Local Optima Network (LON) analysis. LONs capture global patterns in fitness landscapes. CSOPs have not previously been subject to fitness landscape analysis. We fill this gap: LONs are constructed and studied for meaningful structure. The CSOP formulation presents novel challenges and questions for the LON model because there are infeasible regions in the fitness landscape and an unknown global optimum; it also brings a topic from healthcare to LON analysis. Two LON Construction algorithms are proposed for sampling CSOP fitness landscapes: a Markov-Chain Construction Algorithm and a Hybrid Construction Algorithm. The results provide new insight into LONs of highly-constrained spaces, and into the proficiency of search operators on the CSOP. Iterated Local Search and Memetic Search, which are the foundations for the LON algorithms, are found to markedly out-perform a Genetic Algorithm from the literature

Shift Scheduling and Employee Rostering: An Evolutionary Ruin & Stochastic Recreate Solution

For decades, since the inception of the field, scheduling problems have been solved with a variety of techniques. Many proven algorithms to these problems exist; however, there is no single method to solve all the vast variety of problems that exist across many sub-fields with differing datasets. In this paper we explore the use of an Evolutionary Ruin & Stochastic Recreate algorithm, with a Simulated Annealing control mechanism, to a real-world employee scheduling problem and its ability to solve this problem to near optimality. The combinatorial possibilities of parameterisation are very large-the Taguchi design of experiments method is used to examine a subset of those possibilities within a limited runtime budget. Evolutionary Ruin and Stochastic Recreate has not previously been applied to the specific scheduling domain of employee scheduling and rostering: we investigate the effectiveness of the algorithm with different parameter values and discuss the insight it provides into the runtime effect of the mechanisms of Evolutionary Ruin & Stochastic Recreate

A randomized double-blind control study of early intra-coronary autologous bone marrow cell infusion in acute myocardial infarction: the REGENERATE-AMI clinical trial

Clinical trials suggest that intracoronary delivery of autologous bone marrow-derived cells (BMCs) 1–7 days post-acute myocardial infarction (AMI) may improve left ventricular (LV) function. Earlier time points have not been evaluated. We sought to determine the effect of intracoronary autologous BMC on LV function when delivered within 24 h of successful reperfusion therapy. Methods and results A multi-centre phase II randomized, double-blind, and placebo-controlled trial. One hundred patients with anterior AMI and significant regional wall motion abnormality were randomized to receive either intracoronary infusion of BMC or placebo (1:1) within 24 h of successful primary percutaneous intervention (PPCI). The primary endpoint was the change in left ventricular ejection fraction (LVEF) between baseline and 1 year as determined by advanced cardiac imaging. At 1 year, although LVEF increased compared with baseline in both groups, the between-group difference favouring BMC was small (2.2%; 95% confidence interval, CI: −0.5 to 5.0; P = 0.10). However, there was a significantly greater myocardial salvage index in the BMC-treated group compared with placebo (0.1%; 95% CI: 0.0–0.20; P = 0.048). Major adverse events were rare in both treatment groups. Conclusion The early infusion of intracoronary BMC following PPCI for patients with AMI and regional wall motion abnormality leads to a small non-significant improvement in LVEF when compared with placebo; however, it may play an important role in infarct remodelling and myocardial salvage.UK Stem Cells Foundation, the Heart Cells Foundation, and Barts and the London Charity. Funding to pay the Open Access publication charges for this article was provided by the Barts Cardiovascular Biomedical Research Unit (CVBRU)