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An Innovative GA for VCIM Production Scheduling Optimisation

This thesis is divided into five chapters which focus on different production scheduling problems.

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Remarks:This paper gives the first (universal) exact sampling algorithm thatruns in time that is polynomial in certain parameters associated withthe Markov chain.

Various summary statistics are presented, and estimation and examples of the use of such are given.

In this paper we discuss the implementation of coupling from the past for samplers on a continuous state space; our ultimate objective is Bayesian MCMC with guaranteed convergence.

Scheduling (production processes) - Wikipedia

In this paper, we propose the application of another sampling technique: the Perfect Sampling (PS).

This thesis reports on an innovative production-scheduling model for virtual computer-integrated manufacturing (VCIM) systems. It also describes a robust genetic algorithm for production scheduling in VCIM systems. The model, which is the most comprehensive of its kind to date, is not only capable of supporting collaborative shipment scheduling and handling multiple product orders simultaneously, but also helps cope with multiple objective functions under uncertainties. In turn, the genetic algorithm, characterised by an innovative algorithm structure, chromosome encoding, crossover and mutation, is capable of searching for optimal/suboptimal solutions to the complex optimisation problem in the VCIM production- scheduling model described. Lastly, the effectiveness of the proposed approach is verified in a comprehensive case study.

This thesis reports on an innovative production-scheduling model for virtual computer-integrated manufacturing (VCIM) systems. It also describes a robust genetic algorithm for production scheduling in VCIM systems. The model, which is the most comprehensive of its kind to date, is not only capable of supporting collaborative shipment scheduling and handling multiple product orders simultaneously, but also helps cope with multiple objective functions under uncertainties. In turn, the genetic algorithm, characterised by an innovative algorithm structure, chromosome encoding, crossover and mutation, is capable of searching for optimal/suboptimal solutions to the complex optimisation problem in the VCIM production- scheduling model described. Lastly, the effectiveness of the proposed approach is verified in a comprehensive case study.

Production Scheduling Techniques – A Review | …

As illustrating examples, simulations of the hard-core model and the random-cluster model are presented.

(Postscript)(PDF)Per author's description: This paper introduces the idea of a boundingchain for determining when complete coupling has occurred so thatCoupling From the Past may be run on the chain to obtain exactsamples.

Abstract:Figures are presented to illustrate some examples of iterated random functions of the kind described in the article in this issue by Diaconis and Freedman.

This case arises in comparing applicability of the perfect sampling algorithms of Propp and Wilson and the first author of the present paper.
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  • Applying Lean Principles to Production Scheduling | …

    Abstract:This paper reports some initial investigations of the use of antithetic variates in perfect sampling.

  • Production Scheduling | Scheduling (Production …

    A systematic approach for scheduling production in continuous processing systems

  • Production scheduling tutorial with Excel download for …

    Production-scheduling in Fresh Vegetable Processing Publication Publication. A case study at W. Heemskerk BV

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Production Process – Manufacturing Scheduling

Production Scheduling, extraction sequence of mining blocks in different production periods to maximize profit over the life of the mine and subjected to different constraints, is an important aspect of any mining activity. Mine production scheduling problem can be solved using various approaches, but the best approach is one which can give an optimal result. Production scheduling solely cannot result in a proper planning thus, fleet assignment problem needs to be incorporated into production scheduling problem to have a realistic mine plan. Proper fleet assignment ensures that the fleet is not under or over utilized. Fleet assignment problem is integer type programming since, size of fleet cannot be a floating number. In this thesis, production scheduling and fleet assignment problem are solved using branch and cut algorithm. Production schedule for 4736 blocks from a case study of coal mine is done with a production period of 5 years. Solution time for solving the production scheduling problem was 48.14 hours with an NPV value of Rs 4.45938x1011. Short terms production scheduling is done for one year and the NPV value obtained was Rs 7.59796x1010 with a solution time of 57.539 minutes. Fleet assignment is done for first year and is observed that the size of dumper fleet can be reduced to 30 thus saving huge amount of initial capital investment.

Refinery production planning and scheduling: the …

This paper explores what is possible and what is not, and was thefirst paper to show that it is possible to obtain unbiased samplesfrom the steady state distribution of a finite Markov chain by observingit, provided it is irreducible and one knows how many states it has.

Excel Demand Analytics - production scheduling

Remarks:While technically not a paper on exact sampling, this paperinvestigates how the mixing time of a Markov chain may be inferred byrunning a large number of coupled simulations until they coalesce.

A Review of Production Scheduling (PDF Download …

In this paper we extend coupling from the past to various MCMC samplers on a continuous state space; rather than following the monotone sampling device of Propp and Wilson, our approach uses methods related to gamma-coupling and rejection sampling to simulate the chain, and direct accounting of sample paths to check whether they have coupled.

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