Abstract

This theory-oriented, methodological and conceptual survey explores the application of Multi-Criteria Decision-Making (MCDM) methods in vehicle routing, transportation and robot navigation. Multi-criteria decision aid brings significant added value in applications where robots and autonomous agents execute missions with multiple objectives in multi-cost and multi-criteria environments. Logistic operations and multi-modal transportation tasks, where multiple factors influence mission success, also benefit from multi-criteria decision aid. Decisions are inherently complex, and MCDM methods capture certain aspects of the decision contexts as they inherently encode different contextual priorities. An evaluation on the effectiveness of MCDM methods may prove to be uninformative without information on contextual preferences. Direct MCDM method comparison may fail to reveal insight over method effectiveness without contextual information. The survey presents an interpretive synthesis over decision modeling constructs and introduces a new context-oriented analytical synthesizing perspective to establish a meaningful base for comparison. Through conceptual abstraction over decision roles, latent decision structures and recurring decision patterns, two stable explanatory constructs emerged: ‘governing aspects’and ‘application attitudes’. Governing aspects characterize decision influences, whereas application attitudes characterize decision architectures. We analyze attitudes pertaining to different application domains from the perspective of responsiveness and computation demand, and discuss some key governing aspects, such as robust decision-making and behavior elicitation. We aim to provide a rich landscape of multi-criteria decision scenarios, and identify future research areas based on our findings. The outlined synthesizing framework functions both as a methodological taxonomy and a conceptual compass and case repository for navigating MCDM applications.

IPC Classification

Keywords