Crossdocking studies have mostly been concerned with the physical layout of a crossdock or on a single crossdock. In this work, we study a network of crossdocks taking into consideration delivery and pickup time windows, warehouse capacities and inventory handling costs. Because of the complexity of the problem, local search techniques are developed and used with simulated annealing and tabu se...

In recent years, metaheuristics have been applied with some success to the Unit Commitment (UC) problem. Methods like Simulated Annealing, Tabu Search and Evolutionary Programming can be found in several papers, presenting results that are sufficiently interesting to justify further research in the area. In this paper, a new metaheuristic approach based on GRASP Greedy Randomized Adaptive Searc...

This paper presents several local search heuristics for the problem of scheduling a single machine to minimize total weighted tardiness. We introduce a new binary encoding scheme to represent solutions, together with a heuristic to decode the binary representations into actual sequences. This binary encoding scheme is compared to the usual 'natural' permutation representation for descent, simul...

The performance of a scheduling system, in practice, is not evaluated to satisfy a single objective, but to obtain a trade-off schedule regarding multiple objectives. Therefore, in this research, we make use of one of the multiple objective decision-making methods, a global criterion approach, to develop a multi-objective model for solving FMS scheduling problems with consideration of three per...

This paper introduces Tabu Search in analytical chemistry by applying it to wavelength selection. Tabu Search is a deterministic global optimization technique loosely based on concepts from artificial intelligence. Wavelength selection is a method which can be used for improving the quality of calibration models. Tabu Search uses basic, problem-specific operators to explore a search space, and ...

Local search and its variants simulated annealing and tabu search are widely used heuristics to approximately solve NP-hard optimization problems. To use local search one \simply" has to specify a neighborhood structure and a cost function which has to be optimized. However, from a theoretical point of view, many questions remain unanswered, and one of the most important is: which neighborhood ...

– Recently, four search approaches have emerged for handling complex combinatorial optimization problems: Simulated Annealing, Genetic Algorithms, Tabu Search and Greedy Randomized Search Procedure (GRASP). Based on simple ideas, these heuristics have been extremely efficient in finding near-optimal or optimal solutions for many types of difficult problems [1]. In this paper we apply these appr...

response surface methodology is a common tool in optimizing processes. it mainly concerns situations when there is only one response of interest. however, many designed experiments often involve simultaneous optimization of several quality characteristics. this is called a multiresponse surface optimization problem. a common approach in dealing with these problems is to apply desirability funct...

Since the creation of operations research as a discipline, a continued interest has been in the development of heuristics or approximation algorithms to solve complex combinatorial optimization problems. As many problems have been proven computationally intractable, the heuristic approaches become increasingly important in solving various large practical problems. The most popular heuristics th...

GA genetic algorithm HGA hybrid genetic algorithm SA simulated annealing algorithm ACO ant colony optimization TS tabu search IA immune algorithm GDA great deluge algorithm CEA cellular evolutionary approach NN neural network NFT near feasible threshold UGF universal generating function MSS multi-state system RB/i/j recovery block architecture that can tolerate i hardware and j software faults ...