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A higher resource utilization leads to lower cost and higher cycle time, while a lower resource utilization leads to higher cost and lower waiting time. In this setting, this paper presents a multi-objective optimization approach to compute a set of Pareto-optimal resource allocations for a given process concerning cost and cycle time. The approach heuristically searches through the space of possible resource allocations using a simulation model to evaluate each allocation. Given the high number of possible allocations, it is imperative to prune the search space. Accordingly, the approach incorporates a method that selectively perturbs a resource utilization to derive new candidates that are likely to Pareto-dominate the already explored ones. The perturbation method relies on two indicators: resource utilization and resource impact, the latter being the contribution of a resource to the cost or cycle time of the process. Additionally, the approach incorporates a ranking method to accelerate convergence by guiding the search towards the resource allocations closer to the current Pareto front. The perturbation and ranking methods are embedded into two search meta-heuristics, namely hill-climbing and tabu-search. Experiments show that the proposed approach explores fewer resource allocations to compute Pareto fronts comparable to those produced by a well-known genetic algorithm for multi-objective optimization, namely NSGA-II.<\/jats:p>","DOI":"10.1007\/978-3-030-85440-9_6","type":"book-chapter","created":{"date-parts":[[2021,8,13]],"date-time":"2021-08-13T15:03:36Z","timestamp":1628867016000},"page":"92-108","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Silhouetting the Cost-Time Front: Multi-objective Resource Optimization in Business Processes"],"prefix":"10.1007","author":[{"given":"Orlenys","family":"L\u00f3pez-Pintado","sequence":"first","affiliation":[]},{"given":"Marlon","family":"Dumas","sequence":"additional","affiliation":[]},{"given":"Maksym","family":"Yerokhin","sequence":"additional","affiliation":[]},{"given":"Fabrizio Maria","family":"Maggi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,8,14]]},"reference":[{"key":"6_CR1","unstructured":"Abel, M.: Lightning Fast Business Process Model Simulator. 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