optimization of cutting conditions is a non-linear optimization with constraint and it is very important to the increase of productivity and the reduction of costs. in recent years, several evolutionary and meta-heuristic optimization algorithms were introduced. the cuckoo optimization algorithm (coa) is one of several recent and powerful meta-heuristics which is inspired by the cuckoos and the...

The vehicle routing problem with simultaneous pickup and delivery (VRPSPD) is a well-known combinatorial optimization problem which addresses provided service to a set of customers using a homogeneous fleet of capacitated vehicles. The objective is to minimize the distance traveled. The VRPSPD is an NP-hard combinatorial optimization problem. Therefore, practical large-scale instances of VR...

The vehicle routing problem with simultaneous pickup and delivery (VRPSPD) is a well-known combinatorial optimization problem which addresses provided service to a set of customers using a homogeneous fleet of capacitated vehicles. The objective is to minimize the distance traveled. The VRPSPD is an NP-hard combinatorial optimization problem. Therefore, practical large-scale instances of VR...

In this paper the authors describe a model driven approach for the development of heuristic optimization algorithms. Based on a generic algorithm model, several operators are presented which can be used as algorithm building blocks. In combination with a graphical user interface, this approach provides an interactive and declarative way of engineering complex optimization heuristics. By this me...

This chapter focuses on using a highly detailed simulation model to create a physical security system to detect intrusions by human agents in a building thereby minimizing the expected loss of such intrusions. Security consists of human guards and fixed security cameras. The problem is represented as a binary optimization problem and a new heuristic is proposed to perform the security configura...

In the probabilistic two-dimensional Bin Packing problem (2D-PBPP), one is asked to pack a random number of rectangular items, without overlap and any rotation, into the minimum number of identical square bins. In this paper we consider the re-optimization procedure used for solving probabilistic combinatorial optimization problems and an approximation of this strategy: the redistribution strat...

Abstract: In this work a heuristic optimization algorithm known as the Fruit fly Optimization Algorithm is applied to antenna design problems. The original formulation of the algorithm is presented and it is adapted to array factor and horn antenna optimization problems. Specifically, it is applied to the array factor synthesis of uniformly-fed, non-equispaced arrays and to the profile optimiza...

This chapter discusses rollout algorithms, a sequential approach to optimization problems, whereby the optimization variables are optimized one after the other. A rollout algorithm starts from some given heuristic and constructs another heuristic with better performance than the original. The method is particularly simple to implement, and is often surprisingly e↵ective. This chapter explains t...

This study deals with a new hybrid global–local optimization algorithm named PSOLVER that combines particle swarm optimization (PSO) and a spreadsheet ‘‘Solver” to solve continuous optimization problems. In the hybrid PSOLVER algorithm, PSO and Solver are used as the global and local optimizers, respectively. Thus, PSO and Solver work mutually by feeding each other in terms of initial and sub-i...