• 산업경영시스템학회지
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• 제37권1호
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• pp.133-140
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• 2014

An efficient heuristic for two-vehicle-one-depot problems is developed in this research. Vehicle moving speeds are various along hour based time intervals due to traffic jams of rush hours. Two different heuristics are examined. One is that the delivery area assignment is made using Sweep algorithm for two vehicles by splitting the whole area in half to equally divide all delivery points. The other is using common area by leaving unassigned area between the assigned for two vehicles. The common area is reassigned by two stages to balance the completion time of two vehicle's delivery. The heuristic with common area performed better than the other due to various vehicle moving speeds and traffic jams.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.656-657
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• 2015

Recently, Multi-Objective Optimization of design elements is an important issue in building design. Design variables that considering the specificities of the different environments should use the appropriate algorithm on optimization process. The purpose of this study is to compare and analyze the optimal solution using three evolutionary algorithms and energy modeling simulation. This paper consists of three steps: i)Developing three evolutionary algorithm model for optimization of design elements ; ii) Conducting Multi-Objective Optimization based on the developed model ; iii) Conducting comparative analysis of the optimal solution from each of the algorithms. Including Non-dominated Sorted Genetic Algorithm (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO) and Random Search were used for optimization. Each algorithm showed similar range of result data. However, the execution speed of the optimization using the algorithm was shown a difference. NSGA-II showed the fastest execution speed. Moreover, the most optimal solution distribution is derived from NSGA-II.

• Advances in robotics research
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• 제2권3호
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• pp.247-257
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• 2018

Various studies have been performed to coordinate robots in transporting objects and different artificial intelligence algorithms have been considered in this field. In this paper, we investigate and solve Multi-Robot Transportation problem by using a combined auction algorithm. In this algorithm each robot, as an agent, can perform the auction and allocate tasks. This agent tries to clear the auction by studying different states to increase payoff function. The algorithm presented in this paper has been applied to a multi-robot system where robots are responsible for transporting objects. Using this algorithm, robots are able to improve their actions and decisions. To show the excellence of the proposed algorithm, its performance is compared with three heuristic algorithms by statistical simulation approach.

• 전자공학회논문지A
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• 제29A권4호
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• pp.64-73
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• 1992

This paper presents the design of multi-level logic optimization algorithm and the development of the SMILE system based on the algorithm. Considering the fanin constraints in algorithmic level, SMILE performs global and local optimization in a predefined sequence using heuristic information. Designed under the Sogang Silicon Compiler design environment, SMILE takes the SLIF netlist or Berkeley equation formats obtained from high-level synthesis process, and generates the optimized circuits in the same format. Experimental results show that SMILE produces the promising results for some circuits from MCNC benchmarks, comparable to the popularly used multi-level logic optimization system, MIS.

• 대한산업공학회지
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• 제41권3호
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• pp.233-242
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• 2015

This paper analyzes a multi-product inbound lot-sizing and outbound dispatching problem with multi-vehicle types in a third-party logistics distribution center. The product must be delivered to the customers within the delivery time window and backlogging is not allowed. Replenishing orders are shipped by several types of vehicles with two types of the freight costs, i.e., uniform and decreasing, are considered. The objective of this study is to determine the lot-size and dispatching schedules to minimize the total cost with the sum of inbound and outbound transportation and inventory costs over the entire time horizon. In this study, we mathematically derive a mixed-integer programming model and propose a genetic algorithm (GA1) based on a local search heuristic algorithm to solve large-scale problems. In addition, we suggest a new genetic algorithm (GA2) with an adjusting algorithm to improve the performance of GA1. The basic mechanism of the GA2 is to provide an unidirectional partial move of products to available containers in the previous period. Finally, we analyze the results of GA1 and GA2 by evaluate the relative performance using the gap between the objective values of CPLEX and the each algorithm.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.25-32
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• 2023

Decision-making refers to identifying the best alternative among a set of alternatives. When a set of criteria are involved, the decision-making is called multi-criteria decision-making (MCDM). In some cases, the involved criteria may be prioritized by the human decision-maker, which determines the importance degree for each criterion; hence, the decision-making becomes prioritized multi-criteria decision-making. The essence of prioritized MCDM is raking the different alternatives concerning the criteria and selecting best one(s) from the ranked list. This paper introduces a generic multi-level algorithm for ranking multiple alternatives in prioritized MCDM problems. The proposed algorithm is implemented by a decision support system for selecting the most critical short-road requests presented to the transportation ministry in the Kingdom of Saudi Arabia. The ranking results show that the proposed ranking algorithm achieves a good balance between the importance degrees determined by the human decision maker and the score value of the alternatives concerning the different criteria.

• 산업경영시스템학회지
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• 제43권2호
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• pp.79-86
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• 2020

To make a satisfactory decision regarding project scheduling, a trade-off between the resource-related cost and project duration must be considered. A beneficial method for decision makers is to provide a number of alternative schedules of diverse project duration with minimum resource cost. In view of optimization, the alternative schedules are Pareto sets under multi-objective of project duration and resource cost. Assuming that resource cost is closely related to resource leveling, a heuristic algorithm for resource capacity reduction (HRCR) is developed in this study in order to generate the Pareto sets efficiently. The heuristic is based on the fact that resource leveling can be improved by systematically reducing the resource capacity. Once the reduced resource capacity is given, a schedule with minimum project duration can be obtained by solving a resource-constrained project scheduling problem. In HRCR, VNS (Variable Neighborhood Search) is implemented to solve the resource-constrained project scheduling problem. Extensive experiments to evaluate the HRCR performance are accomplished with standard benchmarking data sets, PSPLIB. Considering 5 resource leveling objective functions, it is shown that HRCR outperforms well-known multi-objective optimization algorithm, SPEA2 (Strength Pareto Evolutionary Algorithm-2), in generating dominant Pareto sets. The number of approximate Pareto optimal also can be extended by modifying weight parameter to reduce resource capacity in HRCR.

• 한국경영과학회지
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• 제19권3호
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• pp.63-79
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• 1994

Many vehicle fleet planning systems have been suggested to minimize the routing distances of vehicles or reduce the transportation cost. But the more considerations the method takes, the higher complexites are involved in a large number of practical situations. The purpose of this paper is to vehicle fleet planning system. This paper is considered multi-objective optimization. The vehicle fleet planning system developed by this study involves such complicated and restricted conditions as one depot, multiple nodes (demand points), multiple vehicle types, multipel order items, and other many restrictions for operating vehicles. The proposed algorithm is compared with the nearest neighbor heuristic (NNH) and the savings heuristic (SAH) algorithm in terms of total logistics cost and driving time. This method constructs a route with a minimum number of vehicles for a given demand. This method can be used to any companys which vehicle fleet planning system under circumstances considered in this paper.

• 산업경영시스템학회지
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• 제11권17호
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• pp.39-46
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• 1988

This Paper is concerned with a man-multi machine assignment problem to minimize idle time. Assuming different types of semi-automatic machines with deterministic service-processing time, the problem approaches by sequential dependent one operator can handle several machines, where determine optimal range the cost of idle labor and machine time is to be minimized in preparing a work schedule. The Procedure, to establish man-machine assignment model, and it's results are: (1) Objective function to minimize opportunity loss cost, which is happened by idle time, is verified recursive process through heuristic method. (2) The algorithm, is programmed by BASIC language for personal computer, and a numerical example is given to illustrate the heuristic algorithm. This study will be helpful to enhance productivity of Shopflooras a result of increasing the efficiencies of both operator and machine.

• 대한산업공학회지
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• 제20권4호
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• pp.23-35
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• 1994

Efficient operation of a component placement machine with a multi-head in a PCB assembly process is considered. The problem consists of two subproblems, which are the optimal allocation of the component tape reels in the rack and the optimal mounting sequence of the components on a printed circuit board. We analyze the problem and propose a heuristic algorithm to solve it. The heuristic can be used for the one head case too. Computational experiences on some real world problems show the effectiveness of the heuristic in terms of speed and solution quality.