Search results for: Daryl Essam

Items from 1 to 20 out of 40 results

article

A mathematical modelling approach for managing sudden disturbances in a three-tier manufacturing supply chain

Sanjoy Kumar Paul, Ruhul Sarker, Daryl Essam, Paul Tae-Woo Lee

Annals of Operations Research > 2019 > 280 > 1-2 > 299-335

This paper aims to develop a recovery planning approach in a three-tier manufacturing supply chain, which has a single supplier, manufacturer, and retailer under an imperfect production environment, in which we consider three types of sudden disturbances: demand fluctuation, and disruptions to production and raw material supply, which are not known in advance. Firstly, a mathematical model is developed...

article

A new methodology for the open-pit mine production scheduling problem

Mehran Samavati, Daryl Essam, Micah Nehring, Ruhul Sarker

Omega > 2018 > 81 > C > 169-182

The open pit mine production scheduling problem (OPMPSP) consists of scheduling the extraction of a mineral deposit that is broken into a number of smaller segments, or blocks, such that the net present value (NPV) of the operation is maximised. This problem has been formulated as an integer programming (IP) model, involving both knapsack and precedence constraints. However, due to the large number...

article

Multiple-order permutation flow shop scheduling under process interruptions

Humyun Fuad Rahman, Ruhul Sarker, Daryl Essam

The International Journal of Advanced Manufacturing Technology > 2018 > 97 > 5-8 > 2781-2808

The permutation flow shop problem is a complex combinatorial optimization problem. Over the last few decades, a good number of algorithms have been proposed to solve static permutation flow shop problems. However, in practice, permutation flow shop problems are not static but rather are dynamic because the orders (where each order contains multiple jobs) arrive randomly for processing and the operation...

article

A methodology for the large-scale multi-period precedence-constrained knapsack problem: an application in the mining industry

Mehran Samavati, Daryl Essam, Micah Nehring, Ruhul Sarker

International Journal of Production Economics > 2017 > 193 > C > 12-20

This paper considers a generalization of the precedence-constrained knapsack problem known as multi-period precedence-constrained knapsack, in which the decision maker faces a horizon of several periods. Associated with each period is a capacity limit that cannot be exceeded by items chosen in that specific period. The motivation for studying this problem comes from a recognized problem in the mining...

article

A quantitative model for disruption mitigation in a supply chain

Sanjoy Kumar Paul, Ruhul Sarker, Daryl Essam

European Journal of Operational Research > 2017 > 257 > 3 > 881-895

In this paper, a three-stage supply chain network, with multiple manufacturing plants, distribution centers and retailers, is considered. For this supply chain system we develop three different approaches, (i) an ideal plan for an infinite planning horizon and an updated plan if there are any changes in the data, (ii) a predictive mitigation planning approach for managing predictive demand changes,...

article

A local branching heuristic for the open pit mine production scheduling problem

Mehran Samavati, Daryl Essam, Micah Nehring, Ruhul Sarker

European Journal of Operational Research > 2017 > 257 > 1 > 261-271

This paper considers the well-known open pit mine production scheduling problem (OPMPSP). Given a discretisation of an orebody as a block model, this problem seeks a block extraction sequence that maximises the net present value (NPV) over a horizon of several periods. In practical applications, the number of blocks can be large, and therefore, the problem can be difficult to solve. It is even more...

chapter

A Genetic Algorithm with Priority Rules for Solving Job-Shop Scheduling Problems

S. M. Kamrul Hasan, Ruhul Sarker, Daryl Essam, David Cornforth

Studies in Computational Intelligence > Natural Intelligence for Scheduling, Planning and Packing Problems > 55-88

The Job-Shop Scheduling Problem (JSSP) is one of the most difficult NP-hard combinatorial optimization problems. In this chapter, we consider JSSPs with an objective of minimizing makespan while satisfying a number of hard constraints. First, we develop a genetic algorithm (GA) based approach for solving JSSPs. We then introduce a number of priority rules to improve the performance of GA, such as...

chapter

Analysing the Regularity of Genomes Using Compression and Expression Simplification

Jungseok Shin, Moonyoung Kang, R. I. (Bob) McKay, Xuan Nguyen, more

Lecture Notes in Computer Science > Genetic Programming > Posters > 251-260

We propose expression simplification and tree compression as aids in understanding the evolution of regular structure in Genetic Programming individuals. We apply the analysis to two previously-published algorithms, which aimed to promote regular and repeated structure. One relies on subtree duplication operators, the other uses repeated evaluation during a developmental process. Both successfully...

chapter

The Role of Explicit Niching and Communication Messages in Distributed Evolutionary Multi-objective Optimization

Lam T. Bui, Daryl Essam, Hussein A. Abbass

Studies in Computational Intelligence > Parallel and Distributed Computational Intelligence > 181-206

This chapter is dedicated to an investigation on the role of explicit niching and communication messages in distributed evolutionary multi-objective optimization. Localization is employed to implement explicit niching. Several options are selected for communication messages including non-dominated solutions and statistics such as the centroid of the non-dominated set, the direction of improvement,...

chapter

Building on Success in Genetic Programming: Adaptive Variation and Developmental Evaluation

Tuan-Hao Hoang, Daryl Essam, Bob McKay, Nguyen-Xuan Hoai

Lecture Notes in Computer Science > Advances in Computation and Intelligence > Evolutionary Algorithms and Operators > 137-146

We investigate a developmental tree-adjoining grammar guided genetic programming system (DTAG3P⁺), in which genetic operator application rates are adapted during evolution. We previously showed developmental evaluation could promote structured solutions and improve performance in symbolic regression problems. However testing on parity problems revealed an unanticipated problem, that good building...

chapter

Dual Guidance in Evolutionary Multi-objective Optimization by Localization

Lam T. Bui, Kalyanmoy Deb, Hussein A. Abbass, Daryl Essam

Lecture Notes in Computer Science > Simulated Evolution and Learning > Evolutionary Optimisation > 384-391

In this paper, we propose a framework using local models for multi-objective optimization to guide the search heuristic in both the decision and objective spaces. The localization is built using a limited number of adaptive spheres in the decision space. These spheres are usually guided, using some direction information, in the decision space towards the areas with non-dominated solutions. We use...

chapter

Learning General Solutions through Multiple Evaluations during Development

Tuan-Hao Hoang, R. I. (Bob) McKay, Daryl Essam, Xuan Hoai Nguyen

Lecture Notes in Computer Science > Evolvable Systems: From Biology to Hardware > Development > 201-212

In this paper, we investigate whether performing multiple evaluations during development – a technique we call Evolutionary Developmental Evaluation (EDE) – could help developmental Genetic Programming (GP) evolve general solutions, solving not only the original (training) problem, but also unseen similar problems (with higher degrees of complexity). The hypothesis is tested on two families of regression...

chapter

Genetic Transposition in Tree-Adjoining Grammar Guided Genetic Programming: The Duplication Operator

Nguyen Xuan Hoai, Robert Ian Bob McKay, Daryl Essam, Hoang Tuan Hao

Lecture Notes in Computer Science > Genetic Programming > Talks > 108-119

We empirically investigate the use of dual duplication/truncation operators both as mutation operators and as generic local search operators, in combination with genetic search in a tree adjoining grammar guided genetic programming system (TAG3P). The results show that, on the problems tried, duplication/truncation works well as a mutation operator but not reliably when the complexity of the problem...

chapter

A Survey of Probabilistic Model Building Genetic Programming

Yin Shan, Robert I. McKay, Daryl Essam, Hussein A. Abbass

Studies in Computational Intelligence > Scalable Optimization via Probabilistic Modeling > 121-160

article

A reactive mitigation approach for managing supply disruption in a three-tier supply chain

Sanjoy Kumar Paul, Ruhul Sarker, Daryl Essam

Journal of Intelligent Manufacturing > 2018 > 29 > 7 > 1581-1597

In this paper, we develop a quantitative reactive mitigation approach for managing supply disruption for a supply chain. We consider a three-tier supply chain system with multiple raw material suppliers, a single manufacturer and multiple retailers, where the system may face sudden disruption in its raw material supply. First, we develop a mathematical model that generates a recovery plan after the...

article

A real-time order acceptance and scheduling approach for permutation flow shop problems

Humyun Fuad Rahman, Ruhul Sarker, Daryl Essam

European Journal of Operational Research > 2015 > 247 > 2 > 488-503

The Permutation Flow Shop Scheduling Problem (PFSP) is a complex combinatorial optimization problem. PFSP has been widely studied as a static problem using heuristics and metaheuristics. In reality, PFSPs are not usually static, but are rather dynamic, as customer orders are placed at random time intervals. In the dynamic problem, two tasks must be considered: (i) should a new order be accepted? and...

article

A genetic algorithm for permutation flow shop scheduling under make to stock production system

Humyun Fuad Rahman, Ruhul Sarker, Daryl Essam

Computers & Industrial Engineering > 2015 > 90 > C > 12-24

The permutation flow shop scheduling is a well-known combinatorial optimization problem that arises in many manufacturing systems. Over the last few decades, permutation flow shop problems have widely been studied and solved as a static problem. However, in many practical systems, permutation flow shop problems are not really static, but rather dynamic, where the challenge is to schedule n different...

article

Decomposition-based evolutionary algorithm for large scale constrained problems

Eman Sayed, Daryl Essam, Ruhul Sarker, Saber Elsayed

Information Sciences > 2015 > 316 > Complete > 457-486

Cooperative Coevolutionary algorithms (CC) have been successful in solving large scale optimization problems. The performance of CC can be improved by decreasing the number of interdependent variables among decomposed subproblems. This is achieved by first identifying dependent variables, and by then grouping them in common subproblems. This approach has potential because so far no grouping technique...

article

Managing disruption in an imperfect production–inventory system

Sanjoy Kumar Paul, Ruhul Sarker, Daryl Essam

Computers & Industrial Engineering > 2015 > 84 > Complete > 101-112

In this paper, a disruption recovery model is developed for an imperfect single-stage production–inventory system. For it, the system may unexpectedly face either a single disruption or a mix of multiple dependent and/or independent disruptions. The system is usually run according to a user defined production–inventory policy. We have formulated a mathematical model for rescheduling the production...

article

A disruption recovery plan in a three-stage production-inventory system

Sanjoy Kumar Paul, Ruhul Sarker, Daryl Essam

Computers and Operations Research > 2015 > 57 > Complete > 60-72

This paper proposes a recovery plan for managing disruptions in a three-stage production-inventory system under a mixed production environment. First, a mathematical model is developed to deal with a disruption at any stage while maximizing total profit during the recovery-time window. The model is solved after the occurrence of a disruption event, with changed data used to generate a revised plan...

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INFONA - science communication portal

Search results for: Daryl Essam

A mathematical modelling approach for managing sudden disturbances in a three-tier manufacturing supply chain

A new methodology for the open-pit mine production scheduling problem

Multiple-order permutation flow shop scheduling under process interruptions

A methodology for the large-scale multi-period precedence-constrained knapsack problem: an application in the mining industry

A quantitative model for disruption mitigation in a supply chain

A local branching heuristic for the open pit mine production scheduling problem

A Genetic Algorithm with Priority Rules for Solving Job-Shop Scheduling Problems

Analysing the Regularity of Genomes Using Compression and Expression Simplification

The Role of Explicit Niching and Communication Messages in Distributed Evolutionary Multi-objective Optimization

Building on Success in Genetic Programming: Adaptive Variation and Developmental Evaluation

Dual Guidance in Evolutionary Multi-objective Optimization by Localization

Learning General Solutions through Multiple Evaluations during Development

Genetic Transposition in Tree-Adjoining Grammar Guided Genetic Programming: The Duplication Operator

A Survey of Probabilistic Model Building Genetic Programming

A reactive mitigation approach for managing supply disruption in a three-tier supply chain

A real-time order acceptance and scheduling approach for permutation flow shop problems

A genetic algorithm for permutation flow shop scheduling under make to stock production system

Decomposition-based evolutionary algorithm for large scale constrained problems

Managing disruption in an imperfect production–inventory system

A disruption recovery plan in a three-stage production-inventory system

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