<p>The minimum adjustment strategy has been widely used to build optimization frameworks for consistency improvement and consensus-reaching in group decision making with reciprocal preference relations. However, numerous optimal solutions often exist for previous minimum-adjustment-based optimization frameworks, and some could lead to contradictory decision outcomes (i.e., contradictory ranking orders of alternatives). It is important to find the most appropriate result from the minimum-adjustment strategy-based optimal solutions for consistency improvement and consensus-reaching. In this study, existing minimum-adjustment-based optimization frameworks for consistency improvement and consensus-reaching with additive reciprocal preference relations (ARPRs) are analyzed and their shortcomings are identified. A new minimum-adjustment-based framework consisting of three sequential optimization models is proposed to improve the additive consistency of an ARPR, and a new minimum-adjustment-based framework comprising three sequential optimization models is developed to reach group consensus together with controlling individual consistency for group decision making with ARPRs. The sequential optimization models are transformed equivalently into linear programs under continuous bipolar scales and into integer linear programs under discrete bipolar scales. Subsequently, a sequential optimization-based interactive consistency improvement procedure and a sequential optimization-based interactive consensus-reaching procedure are presented. Three numerical illustrations with comparative studies are supplied to validate the presented models.</p>