G	a complete graph representing the smart farm
V	the set of feed buckets in the farm
E	the set of edges of the complete graph G
LB	the lower bound
UB	the upper bound
Gm	a complete graph representing the smart farm with feed buckets lacking feed
Vm	the set of feed buckets lacking feed in the farm, include the starting and the final return point of the feeding robot
V 1	the set of feed buckets in the farm
Em	the set of edges of the complete graph Gm
B	a complete path of the feeding robot
PLB	partial lower bound
LBm−k	lower bound of energy consumption of non driving path points
C(Bk)	energy consumption of the determined path
Vk	the determined path that feeding robot has traveled
Bk	the undetermined path that feeding robot has not traveled
OX	order crossover operator
CX	cycle crossover operator
LB1	the lower bound obtained by using the approach proposed in this study
LB2	the lower bound of energy consumption obtained by the minimum spanning tree algorithm
R	the exact result of energy consumption
UB1	the upper bound of energy consumption obtained by the Christofides’s Heuristic algorithm
UB2	the upper bound of energy consumption obtained by greedy algorithm
B-B1	the branch and bound algorithm proposed in this study
B-B2	change the calculation method of obtaining the upper bound of B-B1 to the greedy algorithm, and the rest is same as B-B2
B-B3	change the calculation method of obtaining the lower bound of B-B1 to the minimum spanning tree method, and the rest is same as B-B2
GA-1	the double-crossing operator genetic algorithm based on the upper bound of energy consumption described in this study
GA-2	genetic algorithm with only use order crossover operator as its crossover operator