During wartime, the operation of engineering equipment plays a pivotal role in bolstering the combat prowess of military units. To fully harness this combat potential, it is imperative to provide efficient support precisely when and where it is needed most. While previous research has predominantly focused on optimizing equipment combinations to expedite individual mission performance, our model considers routing challenges encompassing multiple missions and temporal constraints. We implement a comprehensive analysis of potential wartime missions and developed a routing model for the operation of engineering equipment that takes into account multiple missions and their respective time windows of required start and completion time. Our approach focused on two primary objectives: maximizing overall capability and minimizing mission duration, all while adhering to a diverse set of constraints, including mission requirements, equipment availability, geographical locations, and time constraints.

Amphibious operations represent a pivotal military maneuver involving the transfer of landing forces via ships, boats, and aircraft from sea to land. The success of such operations can be the decisive factor in the outcome of a war. Nevertheless, planning an amphibious assault is an intricate and formidable task, demanding careful consideration of numerous variables. This complexity is particularly evident in the formulation of loading plans for troops and equipment onto naval vessels. Historical accounts underscore the profound repercussions of errors in planning and loading on the execution of these operations. In pursuit of efficient loading procedures characterized by precision and time-effectiveness, our study has delved into the realm of optimization modeling. Employing a mixed-integer mathematical programming approach, this optimization model offers a valuable tool to streamline and enhance the preparatory phase of amphibious operations.

The ROK Army must detect the enemy’s location and the type of artillery weapon to respond effectively at wartime. This paper proposes a radar positioning model by applying a scenario-based robust optimization method i.e., binary integer programming. The model consists of the different types of radar, its available quantity and specification. Input data is a combination of target, weapon types and enemy position in enemy’s attack scenarios. In this scenario, as the components increase by one unit, the total number increases exponentially, making it difficult to use all scenarios. Therefore, we use partial scenarios to see if they produce results similar to those of the total scenario, and then apply them to case studies. The goal of this model is to deploy an artillery locating radar that maximizes the detection probability at a given candidate site, based on the probability of all possible attack scenarios at an expected enemy artillery position. The results of various experiments including real case study show the appropriateness and practicality of our proposed model. In addition, the validity of the model is reviewed by comparing the case study results with the detection rate of the currently available radar deployment positions of Corps. We are looking forward to enhance Korea Artillery force combat capability through our research.