Applications of particle swarm optimisation in integrated process planning and scheduling

Guo, Ying; Li, W. D.; Mileham, A R; Owen, Geraint

doi:10.1016/j.rcim.2007.12.002

Cited by 177 publications

(64 citation statements)

References 24 publications

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“…The basic IPPS problem can be defined as follows [7]: "Given a set of parts that are to be processed on machines with operations including alternative manufacturing resources, select suitable manufacturing resources and sequences of operations to determine a schedule in which the precedence constraints among operations can be satisfied and the corresponding objectives can be achieved. "…”

Section: Literature Reviewmentioning

confidence: 99%

A Mathematical Model for Multiworkshop IPPS Problem in Batch Production

Yang

et al. 2018

Mathematical Problems in Engineering

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Integrated Process Planning and Scheduling (IPPS) problem is an important issue in production scheduling. Actually, there exit many factors affecting scheduling results. Many types of workpieces are commonly manufactured in batch production. Moreover, due to differences among process methods, all processes of a workpiece may not be performed in the same workshop or even in the same factory. For making IPPS problem more in line with practical manufacturing, this paper addresses an IPPS problem with batches and limited vehicles (BV-IPPS). An equal batch splitting strategy is adopted. A model for BV-IPPS problem is established. Makespan is the objective to be minimized. For solving the complex problem, a particle swarm optimization (PSO) with a multilayer encoding structure is proposed. Each module of the algorithm is designed. Finally, case studies have been conducted to validate the model and algorithm.

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Section: Literature Reviewmentioning

confidence: 99%

A Mathematical Model for Multiworkshop IPPS Problem in Batch Production

Yang

et al. 2018

Mathematical Problems in Engineering

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“…Among them, PSOs have been greatly adopted during recent years in practical domains [28,29]. The Particle Swarm Optimization (PSO) is a population-based optimization algorithm based on the benchmarking of social interactions such as bird ocking or sh school.…”

Section: Improved Particle Swarm Optimization (Ipso)mentioning

confidence: 99%

Integrated production and distribution scheduling for perishable products

Marandi

Zegordi

2017

Scientia Iranica

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Abstract. This study is concerned with how the quality of perishable products can be improved by shortening the time interval between production and distribution. Since special types of food, such as dairy products, decay fast, the Integration of Production and Distribution Scheduling (IPDS), is investigated. This article deals with a variation of IPDS that contains a short shelf life product; hence, there is no inventory of the product in the process. Once a speci c amount of the product is produced, it must be transported with the least transportation time directly to various customer positions within its limited lifespans to minimize the delivery and tardy costs required to complete producing and distributing of the product to satisfy the demand of customers within the limited deadline. After developing a mixed-integer nonlinear programming model of the problem, because it is NP-hard, an Improved Particle Swarm Optimization (IPSO) is proposed. IPSO performance is compared with commercial optimization software for small-size and moderate-size problems. For large-size ones, it is compared with the genetic algorithm existing in the literature. Computational experiments show the e ciency and e ectiveness of the proposed IPSO in terms of both the quality of the solution and the time of achieving the best solution.

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“…Zhang et al (2008) presented an improved PSO algorithm (IPSO) based on the "all different" constraint to solve the flow shop scheduling problem with the aim of minimizing make span. Guo et al (2009) developed a problem on integration of process planning, scheduling of manufacturing field using PSO algorithm. Shao et al (2009) used a modified genetic algorithm based approach to integrate the process planning and scheduling of manufacturing systems in order to achieve an improved performance.…”

Section: Fig 1 Image Showing Various Tool Combinations Required To mentioning

confidence: 99%

Optimization of hole-making operations for injection mould using particle swarm optimization algorithm

Dalavi¹,

Pawar²,

Singh³

2015

10.5267/j.ijiec

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Optimization of hole-making operations plays a crucial role in which tool travel and tool switch scheduling are the two major issues. Industrial applications such as moulds, dies, engine block etc. consist of large number of holes having different diameters, depths and surface finish. This results into to a large number of machining operations like drilling, reaming or tapping to achieve the final size of individual hole. Optimal sequence of operations and associated cutting speeds, which reduce the overall processing cost of these hole-making operations are essential to reach desirable products. In order to achieve this, an attempt is made by developing an effective methodology. An example of the injection mould is considered to demonstrate the proposed approach. The optimization of this example is carried out using recently developed particle swarm optimization (PSO) algorithm. The results obtained using PSO are compared with those obtained using tabu search method. It is observed that results obtained using PSO are slightly better than those obtained using tabu search method.

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Applications of particle swarm optimisation in integrated process planning and scheduling

Cited by 177 publications

References 24 publications

A Mathematical Model for Multiworkshop IPPS Problem in Batch Production

A Mathematical Model for Multiworkshop IPPS Problem in Batch Production

Integrated production and distribution scheduling for perishable products

Optimization of hole-making operations for injection mould using particle swarm optimization algorithm

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