This study integrates the analytic hierarchy process method, multi-choice goal programming (MCGP), and multi-segment goal programming (MSGP) as a new model to resolve the problem of customized suggestions on exercise plans and diet meals. For personal diet decision support (PDDS), a model-based system is implemented to solve both the exercise selection and diet meals problems. Moreover, the novel pseudo-integer (PI) technique is proposed to solve the large size of PDDS problem efficiently. Also, the MCGP-U technique is adopted to consider users’ risk attitude in the decision-making of diet and exercise.It is intended to help people design their daily personal diet menus and exercise suggestions in achieving their weight loss goals and satisfying the requirements of a balanced diet. The proposed model has the following contributions: (1) it provides a customized exercise plan according to the user’s personal needs of exercise preference and risk attitudes, (2) it allows users to design their daily diet menu according to their individual needs for calories and nutrients, (3) it offers a novel PI method that can easily solve large-sized PDDS problem efficiently, (4) it adopts the MCGP-U technique to consider PDDS’s qualitative issue, and (5) it provides the total solution of exercise and meal suggestion for users to achieve the goal of weight loss. These advantages are of great help to both diabetic patients and healthy people. This improves the healthcare services in developed and developing countries considering multiple qualitative and quantitative criteria.
Read full abstract