Due to copyright restrictions, the access to the full text of this article is only available via subscription.In this study we undertake the optimization of chip shooter component placement machines which became popular in assembling printed circuit boards (PCB) in recent years. A PCB is usually a rectangular plastic board on which the electrical circuit to be used in a particular electronic equipment is printed. The overall optimization of the chip shooter placement machines leads to a very complicated optimization problem which we formulate here for the first time (without any simplifying assumptions). However, it is possible to decompose the problem into placement sequencing problem and feeder configuration problem which turn out to be sequence dependent traveling salesman problem (SDTSP) and Quadratic Assignment Problem (QAP), respectively. We use simulated annealing metaheuristic approach and the heuristics developed for the SDTSP in an earlier study to solve these two problems in an iterative manner. We also attempt to solve the combined overall optimization problem by simulated annealing and artificial bee colony metaheuristics and compare their performances with the iterative approach. The results are in favor of iterative approach.TÜBİTAK ; Marmara University Scientific Research Committe
We consider a path planning problem wherein an agent needs to swiftly navigate from a source to a destination through an arrangement of obstacles in the plane. We suppose the agent has a limited neutralization capability in the sense that it can safely pass through an obstacle upon neutralization at a cost added to the traversal length. The agent's goal is to find the sequence of obstacles to be neutralized en route that minimizes the overall traversal length subject to the neutralization limit. We call this problem the obstacle neutralization problem (ONP), which is essentially a variant of the intractable weight-constrained shortest path problem in the literature. In this study, we propose a simple, yet efficient and effective suboptimal algorithm for ONP based on the idea of penalty search and we present special cases where our algorithm is provably optimal. Computational experiments involving both real and synthetic naval minefield data are also presented.
This study considers the problem of scheduling casting lines of an aluminium casting and processing plant. In aluminium processing plants, continuous casting lines are the bottleneck resources, i.e. factory throughput is limited by the amount of aluminium that can be cast. The throughput of a casting line might be increased by minimizing total setup time between jobs. The objective is to minimize setup time on production lines for a given time period while balancing workload between production lines to accommodate potential new orders. A mathematical formulation for scheduling jobs to minimize the total setup time while achieving workload balance between the production lines is presented. Since the casting scheduling problem is an NP-hard problem, even with only one casting line, a four-step algorithm to find good solutions in a reasonable amount of time is proposed. In this process, a set of asymmetric travelling salesman problems is followed by a pairwise exchange heuristic. The proposed procedure is applied to a case study using real casting data
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