Three approximation algorithms for solving the generalized segregated storage problem

The paper presents three approximation algorithms for solving the generalized segregated storage problem (GSSP). GSSP involves determining an optimal distribution of goods among a set of storage compartments with the segregation (physical separation) restrictions. GSSP is a new generalization of well-known segregated storage problem. The paper gives problem formulation and proposes three approximation algorithms for solving it: a specialized construction heuristic and two population-based algorithms: an evolutionary algorithm and a population learning algorithm. The algorithms are evaluated in computational experiments. The analysis of variance method was used for statistical analysis of obtained results.