Plot of coverage attenuation function. by Junjie He (700642)

“…Secondly, the nodes of the original location of the fire station were added to the set of nodes of the planned construction of the fire station. …”

Chromosome coding. by Junjie He (700642)

“…Secondly, the nodes of the original location of the fire station were added to the set of nodes of the planned construction of the fire station. …”

Definition of parameters. by Junjie He (700642)

“…Secondly, the nodes of the original location of the fire station were added to the set of nodes of the planned construction of the fire station. …”

Distribution of demand points by level. by Junjie He (700642)

“…Secondly, the nodes of the original location of the fire station were added to the set of nodes of the planned construction of the fire station. …”

S1 Data - by Junjie He (700642)

“…Secondly, the nodes of the original location of the fire station were added to the set of nodes of the planned construction of the fire station. …”

Solution results when p = 8~20. by Junjie He (700642)

“…Secondly, the nodes of the original location of the fire station were added to the set of nodes of the planned construction of the fire station. …”

Solution results for different case sizes. by Junjie He (700642)

“…Secondly, the nodes of the original location of the fire station were added to the set of nodes of the planned construction of the fire station. …”

Table of solutions when <i>p</i> = 7~12. by Junjie He (700642)

“…Secondly, the nodes of the original location of the fire station were added to the set of nodes of the planned construction of the fire station. …”

Definition of variables. by Junjie He (700642)

“…Secondly, the nodes of the original location of the fire station were added to the set of nodes of the planned construction of the fire station. …”

EDLIoT: A method for decreasing energy consumption and latency using scheduling algorithm in Internet of Things by Arash GhorbanniaDelavar (22563696)

Improved optimization results. by Yanchun Li (248761)

“…Therefore, in the emerging industrial supply chain network, a model for the multi-objective problem was made using a meta-heuristic approach, specifically the improved genetic algorithm, which is a type of soft computing. To create the initial population, a hybrid approach that combines topology theory and the random search method was adopted, which resulted in a modification of the conventional single roulette wheel selection procedure. …”

Gene comparison map before and after mutation. by Yanchun Li (248761)

“…Therefore, in the emerging industrial supply chain network, a model for the multi-objective problem was made using a meta-heuristic approach, specifically the improved genetic algorithm, which is a type of soft computing. To create the initial population, a hybrid approach that combines topology theory and the random search method was adopted, which resulted in a modification of the conventional single roulette wheel selection procedure. …”

Recombinant gene map. by Yanchun Li (248761)

“…Therefore, in the emerging industrial supply chain network, a model for the multi-objective problem was made using a meta-heuristic approach, specifically the improved genetic algorithm, which is a type of soft computing. To create the initial population, a hybrid approach that combines topology theory and the random search method was adopted, which resulted in a modification of the conventional single roulette wheel selection procedure. …”

model comparison (Idle/%). by Yanchun Li (248761)

“…Therefore, in the emerging industrial supply chain network, a model for the multi-objective problem was made using a meta-heuristic approach, specifically the improved genetic algorithm, which is a type of soft computing. To create the initial population, a hybrid approach that combines topology theory and the random search method was adopted, which resulted in a modification of the conventional single roulette wheel selection procedure. …”

Original optimization results. by Yanchun Li (248761)

“…Therefore, in the emerging industrial supply chain network, a model for the multi-objective problem was made using a meta-heuristic approach, specifically the improved genetic algorithm, which is a type of soft computing. To create the initial population, a hybrid approach that combines topology theory and the random search method was adopted, which resulted in a modification of the conventional single roulette wheel selection procedure. …”

Operator parameter setting of improved GA. by Yanchun Li (248761)

“…Therefore, in the emerging industrial supply chain network, a model for the multi-objective problem was made using a meta-heuristic approach, specifically the improved genetic algorithm, which is a type of soft computing. To create the initial population, a hybrid approach that combines topology theory and the random search method was adopted, which resulted in a modification of the conventional single roulette wheel selection procedure. …”

Product supply sequence diagram. by Yanchun Li (248761)

“…Therefore, in the emerging industrial supply chain network, a model for the multi-objective problem was made using a meta-heuristic approach, specifically the improved genetic algorithm, which is a type of soft computing. To create the initial population, a hybrid approach that combines topology theory and the random search method was adopted, which resulted in a modification of the conventional single roulette wheel selection procedure. …”

Crossed offspring chromosomes. by Yanchun Li (248761)

“…Therefore, in the emerging industrial supply chain network, a model for the multi-objective problem was made using a meta-heuristic approach, specifically the improved genetic algorithm, which is a type of soft computing. To create the initial population, a hybrid approach that combines topology theory and the random search method was adopted, which resulted in a modification of the conventional single roulette wheel selection procedure. …”

GA iteration graph. by Yanchun Li (248761)

“…Therefore, in the emerging industrial supply chain network, a model for the multi-objective problem was made using a meta-heuristic approach, specifically the improved genetic algorithm, which is a type of soft computing. To create the initial population, a hybrid approach that combines topology theory and the random search method was adopted, which resulted in a modification of the conventional single roulette wheel selection procedure. …”

Graphical user interface for workflow. by Yukako Yamane (9034133)