Abstract

PurposeThe purpose of this paper is to present an operations research (OR) model for planning water distribution tours in disaster relief. Especially in situations after a disaster occurrence, characterized by instability and the immediate need of help, high‐quality decisions have to be made fast. For this reason, it is very useful if planning decisions can be alleviated by a decision support system (DSS) using an efficient multi‐objective metaheuristic as its algorithmic core.Design/methodology/approachThe paper develops a metaheuristic search technique based on evolutionary concepts for a real‐world extension of a multi‐objective covering tour problem.FindingsThe proposed method supports decision makers in finding appropriate compromise solutions with respect to conflicting objectives (e.g. coverage and travel time). With this work, the authors want to reduce the gap between theory and practical applications. They apply OR methods to a real‐world application in the field of disaster relief operations planning.Research limitations/implicationsThe success of the proposed approach depends on the availability of reasonable and useful data. However, data generation in this context represents an upcoming discipline, especially under the circumstances of increasing threat by natural hazards.Practical implicationsWhen the approach is integrated in a DSS, different scenarios can be investigated immediately and presented with a geographic information tool. The most appropriate solution for the decision makers can be realized.Originality/valueHeterogeneous transport modes and different road types were not considered so far in these types of problems.

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