An interactive dynamic multi-objective programming model to support better land use planning

Abstract

This study develops a dynamic multi-objective programming (DMOP) approach to handle problems of optimization under conditions of uncertainty typified by multiple goals and dynamic subsystems. The proposed approach seamlessly integrates multi-objective programming, fuzzy set theory, and system dynamics tools to conduct optimal land use planning in dynamic and complex environmental systems. Based on the DMOP approach, this study constructs an interactive dynamic multi-objective programming model, investigates the connection between land use and future urban development, and incorporates the preferences of decision makers using a compromise index. A case study from Taiwan shows that the proposed modeling framework can accommodate more complete information, allowing improvements to be made in strategic planning for land use.