# Multi-Agent Simulation Environment for Logistics Warehouse Design Based on Self-Contained Agents
## 1 Introduction  
Simulation is a crucial part of designing industrial systems such as logistics warehouses. A logistics warehouse is modeled as a multi-agent system (MAS) that consists of various autonomous subsystems with robots and material-handling equipment. It is generally difficult to analyze the performance of a MAS; thus, it is important to model a warehouse and conduct simulations [1; 2; 3] to design and evaluate the system configuration. There exist several multi-agent simulation environments, of which NetLogo [4] is one of the most widely used. There are an increasing number of logistics warehouses that have introduced the use of several robots and material-handling equipment. Since e-commerce is growing rapidly, the order volume of logistics warehouses has increased [5; 6; 7] worldwide. Despite the workload increase in logistics warehouses, there is a labor-shortage problem [8] in several countries because of the decrease in the number of working-age people. Therefore, there is a growing demand for logistics warehouses to introduce robots and material-handling equipment to automate processes to increase productivity without introducing additional human workers. The development costs of a logistics warehouse simulation model are high because it includes the development of various entities, such as different agents (e.g., material-handling equipment, robots, and humans), the physical space that agents operate in, and the items and boxes that are processed and shipped by the agents. Generally, a multi-agent simulator focuses on the simple agents and an environment for analyzing the emergent behavior of agent systems. The development of a simulationmodel of a logistics warehouse is more complicated than ordinary multi-agent simulation in terms of variation in behavior, complexity of the environment, etc. The simulation model of a logistics warehouse requires high modifiability. In the process of designing a logistics warehouse, it is necessary to estimate the productivity of the various possible designs of the warehouse and choose the appropriate equipment in a reasonable configuration (cooperation of subsystems, location of equipment, etc.) to achieve the design goals. Since prototyping [9] and evaluation of a system configuration is key to effective designing of logistics warehouses, low-cost development of simulation models and their modifiability are important. There is a tradeoff between low-cost development and modifiability [10]. It is common to create modules of simulation models and use/reuse them to lower development costs. Using large modules that have several functionalities can greatly reduce the development burden. However, it is difficult to anticipate the simulation requirements because the developers of the logistics warehouses need to try several scenarios of warehouse designs. As the modules become larger, the possibility of the modules cannot fit into the requirements become higher. However, smaller modules have less impact on development cost reduction. This research aims to provide support for designing and optimizing logistics warehouses by reducing the burden on simulating and evaluating the possible designs to choose the best design options. To realize the objective, we set this study's goal to achieve both low-cost development and high modifiability for logistics warehouses. We propose a simulation modeling environment to realize the goal. To improve the ease of developing logistics warehouse simulation models, a simulation modeling environment is needed that provides the common functionalities for logistics warehouse modeling cost reduction, as well as the architecture that enhances modifiability for design considerations of logistics warehouses. The remainder of this paper is organized as follows. Section 2 describes the related work of this paper. Section 3 explains the design and concept of our simulation modeling environment. Section 4 describes the prototypical implementation of the proposed simulation modeling environment.