The textile manufacturing industry is energy- and water-intensive, and has a great impact on the environment. Sustainability-oriented innovation can support the transition of the textile sector towards a circular economy. This review investigates how the textile manufacturing chain can benefit from sustainability-driven innovation strategies to achieve the main circular economy goals. The review was conducted using the Scopus and Web of Science scientific databases, and it addresses material, process, and organizational innovations and covers the 2015–2024 time window. Five main areas of innovation emerged from the retrieved papers, including digitalization, the need for innovative product and process design and sustainable raw materials, the use of textile waste as new raw material outside the textile value chain, waste recovery within the value chain and environmental remediation, and organizational innovation. The innovative solutions analyzed improve the sustainability of the textile manufacturing industry and enable the achievement of circular economy goals. Finally, we discuss some concerns about the introduction of the suggested innovations, including the need to apply design principles for recyclability and durability while studying the feasibility of adopting novel materials.

In make-to-order manufacturing environments, production scheduling and outbound transportation are strongly interdependent, particularly when delivery commitments and vehicle departures are fixed. This paper addresses an integrated production-distribution scheduling problem arising in a real-world food packaging company. The production system consists of unrelated parallel machines with sequence-dependent, machine-specific setup times, while outbound transportation involves a heterogeneous fleet of vehicles with limited capacity, fixed delivery departure times, and customer-specific delivery constraints. The objective function combines total weighted delivery tardiness and total setup times. To address the problem, we propose a GRASP metaheuristic that incorporates several local search procedures. Computational experiments on real-world instances demonstrate the effectiveness of the proposed approach in producing high-quality solutions within limited computational times. The proposed approach has been implemented within a decision support system and validated in collaboration with the industrial partner, confirming its effectiveness in real-world decision-making.