## 5 Optimization Problems with Synchronization Issues
Each truck carries one container at a time, containers may be transported by different trucks during their journey from origin to destination, and drivers have to be back at their starting points in due time. Telecommunication networks are another field in which optimization challenges involve synchronization issues in their structure. They require strict frequency and time synchronization between neighboring base stations to accelerate data transfer without overflow, underflow, bit errors, or other adverse effects. This occurs in code division multiple access, global systemfor mobile communications, and universal mobile telecommunications systems. In global positioning systems, the use of signals is also conditioned by the location of antennas to obtain a clear view of the sky [43]. For these reasons, operators are constantly searching for a better synchronization scheme that allows for sharing very accurate timing information reliably and cost-effectively [44]. [PERSON] and [PERSON] [45] study one of the most popular problems in telecommunications, the unit-response (or master-slave) configuration, in which there is a leader (master) and several devices (slaves) that need to synchronize with the leader. This problem is known as master-slave synchronization of chaotic systems. In secure communications, for instance, there is an unknown input--the transmitted information--that is only retrieved for transmission if and only if the master and slave devices are correctly synchronized. Similar situations characterized by the three aspects mentioned above (i.e., high dynamism, limited shared resources, and dependent events) can also be found in cloud computing [46]. Even in this case, limited resources (e.g., servers or endpoints), unexpected requests and the fact that events depend on each other make this problem a perfect target for BR-DEH algorithms. Other fields in which dynamic optimization problems with synchronization issues are encountered, and where BR-DEH algorithms might be helpful, are those involving different agents whose actions depend on each other. For example, problems considering automated storage and retrieval (AS/RS) systems (Section 4). In these systems, a single operation involves many different machines capable of exchanging the unit loads. These machines can be seen as resources in the case of the job shop, since they are limited, shared by different operations, and dependent on each other. Even in this case, when two or more machines share the same path, we need to model interferences among machines (as in the case of AGVs). A similar situation concerns ride-sharing and car-sharing scenarios [47], where other traffic constraints and unexpected requests might be considered to provide solutions suitable for being implemented in real life. In addition, in genetics, optimization problems with synchronization issues occur. This is the case of the so-called consensus genetic mapping of species, which is based on different sources of mapping information. The challenge arises from inter-population differences in the rate of recombination and the distribution of exchanges along chromosomes, variations in the dominance of the markers used, and the use of different subsets of markers in different laboratories. Thus, for instance, [PERSON] et al. [48] model it as a traveling salesman problem with synchronization. For each data set, the goal was to search for the order that gives the minimum sum of recombination distances between adjacent markers. Therefore, given the current availability of data on different real-life networks (e.g., biological, informational, social, etc.) and with complex infrastructures, there can be many variants of optimization problems with synchronization issues associated with the occurrence of different events. This is because many networks have features such as noise-generating disruptions, evolving or changing connections, and fixed structures, but the activation of nodes depends on a related factor.