**1.9 Software tools**

Nowadays computerized techniques are widely used to solve various types of problems in the world. Sometimes some problems become difficult to solve and time-consuming by hand calculation. So by using different software tools, we can

**1.11 Outline of the chapter**

*DOI: http://dx.doi.org/10.5772/intechopen.93665*

*Weapon Target Assignment*

use in this chapter.

problem.

the examples.

**1.12 Conclusion**

**Table 1.**

**183**

*Existing algorithms for several ye.*

This chapter contains four sections in total which is organized as follows:

• In Section 2, we review some relevant papers about weapon's assignment

• In Section 1, we discuss some prerequisites that are required for WTA problem. We also discuss about the types of optimization models, software tools that we

• In Section 3, we discuss the weapon target assignment problem. We formulate the WTA problem. Some existing algorithms are also presented in this chapter. We discuss the real-life applications and present numerical examples of WTAP. We develop a new computer technique by using programming

language AMPL to solve all type of WTA problem in a single framework. Then finally compare the results we get from AMPL to previously solved results of

In this Section, we discussed the relevant preliminaries. In the next Section, we will review some literature about weapons assignment and chance-constrained problem. In this section, we will review some admissible research articles on Weapon Target Assignment Problem. Since the 1950s, the optimal assignment problem of weapons to targets has always been concerned by many countries. The study of WTA problem can be traced back to the 1950s and 1960s when Manne [2] and Day [3] built the model of WTA problem. The present research work on WTA is focused on models and algorithms. In the research on models of WTA, the static WTA

**Researchers Year Proposed Algorithms Implementation WTA** Galat and Simaan 2007 Tabu Dynamic single-objective Lee 2010 VLSN Static single-objective Xin et al. 2010 VP + Tabu Dynamic single-objective Li and Dong 2010 DPSO+SA Dynamic single-objective Chen et al. 2010 SA Static single-objective Fei et al. 2012 Auction Algorithm Static single-objective Liu et al. 2013 MOPSO Static multi-objective Zhang et al. 2014 MOEA/D Static multi-objective Ahner and Parson 2015 Dynamic Programming Dynamic multi-objective Li et al. 2015 NSGA-II, MOEA/D Static multi-objective Driik et al. 2015 MILP Dynamic multi-objective Liang and Kang 2016 CSA Static single-objective Li et al. 2016 MDE Dynamic multi-objective

• In Section 4, we draw a conclusion about our whole chapter.

**Figure 1.** *Codification of SP problems.*

solve problems from small to large scale problem optimally in a short time. There are so many computer-based mathematical programming languages have been used worldwide. Some of the tools that are used to solve optimization problems are **LINDO, LINGO, AMPL, MATLAB, MATHEMATICA, MAPLE, MS EXCEL SOLVER** and **TORA,** etc. In this chapter, we use AMPL and LINGO.
