• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.227-241
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• 2010

A memory module industry's supply chain usually consists of multiple manufacturing sites and multiple distribution centers. In order to fulfill the variety of demands from downstream customers, production planners need not only to decide the order allocation among multiple manufacturing sites but also to consider memory module industrial characteristics and supply chain constraints, such as multiple material substitution relationships, capacity, and transportation lead time, fluctuation of component purchasing prices and available supply quantities of critical materials (e.g., DRAM, chip), based on human experience. In this research, a directed graph-based supply network planning (DGSNP) model is developed for memory module industry. In addition to multi-site order allocation, the DGSNP model explicitly considers production planning for each manufacturing site, and purchasing planning from each supplier. First, the research formulates the supply network's structure and constraints in a directed-graph form. Then, a proposed genetic algorithm (GA) solves the matrix form which is transformed from the directed-graph model. Finally, the final matrix, with a calculated maximum profit, can be transformed back to a directed-graph based supply network plan as a reference for planners. The results of the illustrative experiments show that the DGSNP model, compared to current memory module industry practices, determines a convincing supply network planning solution, as measured by total profit.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.20-37
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• 2020

In this paper, we propose a simulation method based on backward simulation and process-oriented simulation to take into account the characteristics of shipbuilding production, which is an order-based industry with a job shop production environment. The shipyard production planning process was investigated to analyze the detailed process, variables and constraints of mid-term production planning. Backward and process-centric simulation methods were applied to the mid-term production planning process and an improved planning process, which considers the shipbuilding characteristics, was proposed. Based on the problem defined by applying backward process-centric simulation, a system which can conduct Discrete Event Simulation (DES) was developed. The developed mid-term planning system can be linked with the existing shipyard Advanced Planning System (APS). Verification of the system was performed with the actual shipyard mid-term production data for the four ships corresponding to a one-year period.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.1
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• pp.15-39
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• 2009

Advanced planning and scheduling (APS) refers to a manufacturing management process by which raw materials and production capacity are optimally allocated to meet demand. APS is especially well-suited to environments where simpler planning methods cannot adequately address complex trade-offs between competing priorities. However, most scheduling problems of APS in the real world face both inevitable constraints such as due date, capability, transportation cost, set up cost and available resources. In this survey paper, we address three crucial issues in APS, including basic scheduling model, job-shop scheduling (JSP), assembly line balancing (ALB) model, and integrated scheduling models for manufacturing and logistics. Several evolutionary algorithms which adapt to the problems are surveyed and proposed; some test instances based on the practical problems demonstrate the effectiveness and efficiency of evolutionary approaches.

• Phonetics and Speech Sciences
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• v.3 no.4
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• pp.23-31
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• 2011

This paper examines the production patterns of the acquisition of coda consonants in monosyllabic words in English-speaking children with cochlear implants. The data come from the transcribed speech of children with cochlear implants. This study poses three questions. First, do children with cochlear implants acquire onset consonants earlier than codas? Second, do children's productions have a bimoraic-sized constraint that maintains binary feet? Third, what patterns emerge from production of coda consonants? The results revealed that children with cochlear implants acquire onset consonants earlier than codas. With regard to the bimoraic-sized constraints, the productions of vowel type (i.e., monomoraic and bimoraic) were more accurate for monomoraic vowels than bimoraic ones for some children with cochlear implants, although accuracy in vowel productions showed high proportion regardless of vowel types. The variations of coda production exhibited individual differences. Some children produced less sonorant consonants with high frequency and others produced more sonorant ones. The results of this study were similar to those pertaining to children with normal hearing. In the process of coda consonant acquisition, the error patterns of prosody-sensitive production may be regarded as articulatory challenges to produce higher-level prosodic structures.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.194-196
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• 1989

The production costing plays a key role in power system expansion and operations planning especially for the calculation of expected energy, loss of load probability and unserved energy. Therefore, it is crucial to develope a probabilistic production costing algorithm which gives sufficiently precise results within a reasonable computational time. In this respect, a number of methods of solving production simulation have been proposed. In previous paper we proposed the method used Fast Hartley Transform in convolution process with considering only the thermal units. In this paper, the method considering the scheduling of pumped-storage plants and hydro plants with energy constraints is proposed.

• Asian-Australasian Journal of Animal Sciences
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• v.5 no.2
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• pp.309-314
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• 1992

A review of dairy development and crossbreeding programmes in Malaysia since 1953 is undertaken, based on the relevant literature and the writer's experience. The need for higher domestic milk production and the role of crossbreeding in the realization of this objective is explained. A retrospective evaluation is made of the past crossbreeding programmes and of the decision to use temperate dairy breeds for the purpose. Current dairy development under the 'New Economic Policy' of the Malaysian government and the major problems connected with the importation of high-milk producing animals are discussed. To overcome existing constraints, future strategies for crossbreeding and dairy development, based on long-term objectives, are proposed. It is concluded that crossbreeding will only be useful if the introduction of high yielding dairy animals is combined with an improvement of existing husbandry systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.601-602
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• 2006

The primary role of MRP(Material Requirement Planning) is to make a production plan so that we have an exact quantity of right materials on needed time at right place. But the ignorance on capacity constraints makes some problems whenever production schedule is established. To increase the performance of MRP system, a novel approach which is based on new input data structure is suggested. The new input data structure includes all the information about Material BOM, Routing and resource data so that we can easily examine the usage of resources and generate higher performance production plans.

• Journal of the Korea Society for Simulation
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• v.12 no.1
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• pp.59-71
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• 2003

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Management (SCM). One of the key issues in the current SCM research area involves reducing both production and distribution costs. The purpose of this study is to determine the optimum quantity of production and transportation with minimum cost in the supply chain network. We have presented a mathematical model that deals with real world factors and constraints. Considering the complexity of solving such model, we have applied the genetic algorithm approach for solving this model using a commercial genetic algorithm based optimizer. The results for computational experiments show that the real size problems we encountered can be solved in reasonable time.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.43-54
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• 2005

A flexible assembly line (FAL) is a production system that assembles various parts in unidirectional flow line with many constraints and manufacturing flexibilities. In this research we deal with a FAL balancing problem with the objective of minimizing the maximum workload allocated to the stations. However, almost all the existing researches do not appropriately consider various constraints due to the problem complexity. Therefore, this study addresses a balancing problem of FAL with many constraints and manufacturing flexibilities, unlike the previous researches. We use a genetic algorithm (GA) to solve this problem. To apply GA to FAL. we suggest a genetic representation suitable for FAL balancing and devise evaluation method for individual's fitness and genetic operators specific to the problem, including efficient repair method for preserving solution feasibility. After we obtain a solution using the proposed GA. we use a heuristic method for reassigning some tasks of each product to one or more stations. This method can improve workload smoothness and raise work efficiency of each station. The proposed algorithm is compared and analyzed in terms of solution quality through computational experiments.

• Management Science and Financial Engineering
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• v.15 no.1
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• pp.51-69
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• 2009

A network model and a Genetic Algorithm (GA) is proposed to solve the simultaneous estimation of the trip distribution and traffic assignment from traffic counts in the congested networks in a logit-based Stochastic User Equilibrium (SUE). The model is formulated as a problem of minimizing a non-linear objective function with the linear constraints. In the model, the flow-conservation constraints are utilized to restrict the solution space and to force the link flows become consistent to the traffic counts. The objective of the model is to minimize the discrepancies between two sets of link flows. One is the set of link flows satisfying the constraints of flow-conservation, trip production from origin, trip attraction to destination and traffic counts at observed links. The other is the set of link flows those are estimated through the trip distribution and traffic assignment using the path flow estimator in the logit-based SUE. In the proposed GA, a chromosome is defined as a real vector representing a set of Origin-Destination Matrix (ODM), link flows and route-choice dispersion coefficient. Each chromosome is evaluated by the corresponding discrepancies. The population of the chromosome is evolved by the concurrent simplex crossover and random mutation. To maintain the feasibility of solutions, a bounded vector shipment technique is used during the crossover and mutation.