Due to the complexity and the magnitude of optimisation models that appeared in
sustainable supply chain management (SSCM), the use of meta-heuristic algorithms as …

In this paper, we review the milestones in the development of heuristic methods for
optimization over the last 50 years. We propose a critical analysis of the main findings and …

In recent algorithmic family simulates different biological processes observed in Nature in
order to efficiently address complex optimization problems. In the last years the number of …

The fast-growing Internet results in massive amounts of text data. Due to the large volume of
the unstructured format of text data, extracting relevant information and its analysis becomes …

Remanufacturing and recycling of end-of-life products have changed the structure of supply
chain networks, and the option of closed-loop supply chains gains popularity. Growing strict …

Supply chains are large, complex, and often unpredictable. Purchasing and supply
managers and supply chain risk managers need methods and tools to enable them to …

In this paper, we review the milestones in the development of heuristic methods for
optimization over the last 50 years. We propose a critical analysis of the main findings and …

Metaheuristic optimization algorithms are known for their versatility and adaptability, making
them effective tools for solving a wide range of complex optimization problems. They don't …

Abstract Greedy Randomised Adaptive Search Procedure (GRASP) is one of the best-
known metaheuristics to solve complex combinatorial optimisation problems (COPs). This …

The purpose of this chapter is to provide insights into literature on supply chain disruption
research with a specific focus on future research opportunities. A structured meta-literature …