Innovation Decision-Making Under Uncertain Environment

This book presents a cohesive collection of cutting-edge research focused on advanced decision-support methodologies for complex and ambiguous operational contexts. This volume systematically assembles ten pivotal studies employing uncertain decision-making, multi-criteria decision analysis (MCDA), and tailored optimization models to address substantive challenges in supply chain management, sustainable operations, and strategic planning.

The contributions span a rigorous methodological spectrum, including fuzzy PDCA cycles for green performance evaluation, hybrid MCDM frameworks for lean tool selection, and robust optimization for resilient network design. Applications are drawn from critical domains such as healthcare logistics during epidemic response, sustainable supply chain configuration, and large-scale project trade-off analysis under resource constraints. Each chapter demonstrates the translation of theoretical computational models into applied solutions for decision-making under volatility, incomplete information, and multi-objective pressures.

This volume will serve as a significant reference for academics and graduate researchers in management science, operations research, and industrial engineering. It provides a structured examination of how contemporary soft computing and operational research techniques can be leveraged to enhance analytical rigor and strategic outcomes in the face of pervasive environmental uncertainty.

The chapters in this book were published in International Journal of Management Science and Engineering Management.