Seyed Mahdi Homayouni

A genetic algorithm for optimization of integrated scheduling of cranes, vehicles, and storage platforms at automated container terminals

Commonly in container terminals, the containers are stored in yards on top of each other using yard cranes. The split-platform storage/retrieval system (SP-AS/RS) has been invented to store containers more efficiently and to access them more quickly. The integrated scheduling of quay cranes, automated guided vehicles and handling platforms in SP-AS/RS has been formulated and solved using the simulated annealing algorithm in previous literatures. This paper presents a genetic algorithm (GA) to solve this problem more accurately and precisely. The GA includes a new operator to make a random string of tasks observing the precedence relations between the tasks. For evaluating the performance of the GA, 10 small size test cases were solved by using the proposed GA and the results were compared to those from the literature. Results show that the proposed GA is able to find fairly near optimal solutions similar to the existing simulated annealing algorithm. Moreover, it is shown that the proposed GA outperforms the existing algorithm when the number of tasks in the scheduling horizon increases (e.g. 30 to 100).

A STATISTICAL MODEL FOR EXPECTED CYCLE TIME OF SP-AS/RS: AN APPLICATION OF MONTE CARLO SIMULATION

The elimination of international trade barriers, lower tariffs, and shifting centers of global manufacturing and consumption leads to new dynamics in intermodal shipping. Advanced technologies, and in particular, automated storage/retrieval systems (AS/RSs) for designing high-capacity automated container terminals, have been recently proposed as possible candidates for improving the terminals efficiency and meeting the challenges of the future in marine transportation. In this article, the authors present an analytical statistical model for computing expected cycle time of split-platform AS/RS (SP-AS/RS), in order to reduce average handling time of this system. The accuracy of the proposed statistical model is validated by Monte Carlo simulation. The results show that the analytical model is reliable for the design and analysis of the SP-AS/RS.

Multi Objective Optimization of Coordinated Scheduling of Cranes and Vehicles at Container Terminals

According to previous researches, automated guided vehicles and quay cranes in container terminals have a high potential synergy. In this paper, a mixed integer programming model is formulated to optimize the coordinated scheduling of cranes and vehicles in container terminals. Objectives of the model are to minimize total traveling time of the vehicles and delays in tasks of cranes. A genetic algorithm is developed to solve the problem in reasonable computational time. The most appropriate control parameters for the proposed genetic algorithm are investigated in a medium size numerical test case. It is shown that balanced crossover and mutation rates have the best performance in finding a near optimal solution for the problem. Then, ten small size test cases are solved to evaluate the performance of the proposed optimization methods. The results show the applicability of the genetic algorithm since it can find near optimal solutions, precisely and accurately.

Using simulated annealing algorithm for optimization of quay cranes and automated guided vehicles scheduling

Sea port container terminals play an important role in the national and regional economy. The integrated scheduling of handling equipment has been recently investigated in literature to improve the performance of the container terminals. In this paper, an integrated scheduling of quay cranes and automated guided vehicles is formulated as a mixed integer linear programming model. This model minimizes the makespan of all the loading and unloading tasks for a set of cranes in a scheduling problem. Based on the simulated annealing (SA) algorithm, a scheduling method is proposed to solve the problem in a relatively short period of time. Comparison of the respective results of the mathematical model and the SA algorithm evidently shows acceptable performance of the proposed SA algorithm in finding good solutions for practical scheduling problems. Moreover, the effects of three cooling processes and two sets of control parameters on the best solution of the SA are investigated.

A Fuzzy Delphi-Analytical Hierarchy Process Approach for Ranking of Effective Material Selection Criteria

The ability to select the most appropriate materials for a given application is the fundamental challenge faced by a design engineer. The objective of any material selection procedure is to identify appropriate selection criteria and to obtain the most appropriate combination of criteria in conjunction with requirements. Hence, selection of material is a multicriteria decision making problem. This study investigates and evaluates critical material selection criteria in a priority framework using the fuzzy Delphi-analytical hierarchy process method to overcome all shortcomings from AHP and Delphi methods that are common in material selection problem. 75 of the most important criteria for material selection have been collected from the literature. These criteria have been questioned in automobile interior design firms in Iran for car dashboard design. This ranking method would help product designers to decide on appropriate materials in a consistent method. Results indicate that “general” criteria such as availability, quality, risk, and technology are the most important criteria from the viewpoint of Iranian car manufacturers. Other criteria such as financial, technical, social and environmental, and sensorial criteria are relatively important in subsequent ranks.

A hybrid genetic-heuristic algorithm for scheduling of automated guided vehicles and quay cranes in automated container terminals

Containers have been used in past decades increasingly as one of the most important transportation tools. Containers have revolutionized cargo shipping and thus changed the world trade systematically. Container terminals as the transhipment facility play a valuable role in performance of this transportation system. Improvement of this facility has been widely considered in literatures. Automated container terminals (ACTs) have been introduced to pursue this purpose. In ACTs various transport vehicles are automated and integrated to each other. Automated guided vehicles (AGVs) are used in ACTs to handle containers between quay cranes and storage yards. Usually scheduling of the AGVs is known as the key factor to improve the performance of ACTs. This paper proposed a heuristic algorithm to schedule the AGVs concurrently with quay cranes. A genetic algorithm is proposed to optimize the simultaneous scheduling of AGVs and QCs. The results showed that proposed genetic algorithm can be used in practical implications while its running time is reasonably low.

A Fuzzy Genetic Algorithm for Scheduling of Handling/Storage Equipment in Automated Container Terminals

has been studied during past two decades consciously. Genetic algorithms (GAs) have been applied for this optimization problem in many researches. However, the GA is vulnerable to trap in a local optima (results in premature convergence). In this paper a fuzzy logic controller (FLC) is designed to improve the performance of a GA in optimization of integrated scheduling of handling/storage equipment in automated container terminals. The FLC controls crossover and mutation rates of the GA during its generations, which are the main control parameters of the GA to avoid the premature convergence. The numerical results for the small size test cases solved by using the proposed fuzzy genetic algorithm show that solutions found by this algorithm are 2.5% better than the solutions found by the GA. Studies are continuing for better performance of the proposed FGA.

Bonding Technologies in Manufacturing Engineering

Bonding is an important process used in all fields of industry, where the tight joining of two materials is required. It includes a wide variety of processing technologies that can be placed in a framework of chemistry, physics, and materials science. Although most of these bonding processes have only recently appeared in textbooks, the basic phenomena have been known and used for many centuries. Choosing an appropriate bonding process may result in the improved end-use performance, increased efficiency, and greater design flexibility. Through various bonding techniques, this study aims at investigating the following ones: direct bonding, thermocompression bonding, surface activated bonding, eutectic bonding, adhesive bonding, and glass frit bonding. The characteristic features of these techniques with respect to their many-sided aspects and a review of the current state of the art of each technique are briefly outlined in this chapter.