Generative group-based meal planning system and method

A non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:

• receive a request to generate a candidate meal plan, wherein a seed list including one or more ingredients is designated by a cognitive system based on dish classifications, categories of ingredients, and cuisine classifications, wherein the one or more ingredients included in the seed list are incorporated into one or more recipes contained in the candidate meal plan, wherein the number of needed recipes to be included in the candidate meal plan is pre-determined;
• import one or more recipes incorporating the one or more identified ingredients;
• generate, by the cognitive system, one or more parent meal plans each parent meal plan containing the pre-determined number of recipes, wherein the parent meal plan recipes are randomly selected from the identified recipes incorporating the one or more imported ingredients;
• generate one or more child meal plans, wherein each child meal plan is generated by randomly selecting different parent meal plan recipes and combining the selected parent meal plan recipes;
• wherein one or more mutations are strategically inserted by the cognitive system into the one or more child meal plans;
• determine a fitness score for the one or more child meal plans through the utilization of a genetic algorithm, wherein the genetic algorithm comprises a fitness function that considers cost of ingredients, shelf life of ingredients, flavor compatibility of ingredients, waste ingredients, and preparation time as factors in determining the fitness score;
• wherein the cognitive system generates an additional recipe using all the waste ingredients, and the additional recipe is incorporated into the one or more parent meal plans;
• and
• output the candidate meal plan having the chosen number of recipes, wherein the child meal plan having the highest fitness score is selected to be the candidate meal plan;
• wherein generating one or more parent meal plans, generating one or more child meal plans, and determining the fitness score for the one or more child meal plans are repeated for a pre-determined and finite number of iterations, wherein the one or more child meal plans with the highest fitness scores are used as the next generation of one or more parent meal plans.

A system for generative group-based meal planning, comprising:

• a cognitive system having natural language processing capabilities;
• a meal planning processor configured to:
• receive a request to generate a candidate meal plan, wherein a seed list including one or more ingredients is designated by the cognitive system based on dish classifications, categories of ingredients, and cuisine classifications, wherein the one or more ingredients included in the seed list are incorporated into one or more recipes contained in the candidate meal plan, wherein the number of needed recipes to be included in the candidate meal plan is pre-determined;
• import one or more recipes incorporating the one or more identified ingredients;
• generate, by the cognitive system, one or more parent meal plans, each parent meal plan containing the pre-determined number of recipes, wherein the parent meal plan recipes are randomly selected from the identified recipes incorporating the one or more imported ingredients;
• generate one or more child meal plans, wherein each child meal plan is generated by randomly selecting different parent meal plan recipes and combining the selected parent meal plan recipes;
• wherein one or more mutations are strategically inserted by the cognitive system into the one or more child meal plans;
• determine a fitness score for the one or more child meal plans through the utilization of a genetic algorithm, wherein the genetic algorithm comprises a fitness function that considers cost of ingredients, shelf life of ingredients, flavor compatibility of ingredients, waste ingredients, and preparation time as factors in determining the fitness score;
• wherein the cognitive system generates an additional recipe using all the waste ingredients, and the additional recipe is incorporated into the one or more parent meal plans;
• and
• output the candidate meal plan having the chosen number of recipes, wherein the child meal plan having the highest fitness score is selected to be the candidate meal plan;
• wherein generating one or more parent meal plans, generating one or more child meal plans, and determining the fitness score for the one or more child meal plans are repeated for a pre-determined and finite number of iterations, wherein the one or more child meal plans with the highest fitness scores are used as the next generation of one or more parent meal plans.