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12
Greedy Randomized Adaptive Search Procedures
, 2002
"... GRASP is a multistart metaheuristic for combinatorial problems, in which each iteration consists basically of two phases: construction and local search. The construction phase builds a feasible solution, whose neighborhood is investigated until a local minimum is found during the local search phas ..."
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Cited by 647 (82 self)
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GRASP is a multistart metaheuristic for combinatorial problems, in which each iteration consists basically of two phases: construction and local search. The construction phase builds a feasible solution, whose neighborhood is investigated until a local minimum is found during the local search phase. The best overall solution is kept as the result. In this chapter, we first describe the basic components of GRASP. Successful implementation techniques and parameter tuning strategies are discussed and illustrated by numerical results obtained for different applications. Enhanced or alternative solution construction mechanisms and techniques to speed up the search are also described: Reactive GRASP, cost perturbations, bias functions, memory and learning, local search on partially constructed solutions, hashing, and filtering. We also discuss in detail implementation strategies of memorybased intensification and postoptimization techniques using pathrelinking. Hybridizations with other metaheuristics, parallelization strategies, and applications are also reviewed.
A greedy randomized adaptive search procedure for job shop scheduling
 IEEE Trans. on Power Systems
, 2001
"... Abstract. In the job shop scheduling problem (JSP), a finite set of jobs is processed on a finite set of machines. Each job is characterized by a fixed order of operations, each of which is to be processed on a specific machine for a specified duration. Each machine can process at most one job at a ..."
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Cited by 25 (2 self)
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Abstract. In the job shop scheduling problem (JSP), a finite set of jobs is processed on a finite set of machines. Each job is characterized by a fixed order of operations, each of which is to be processed on a specific machine for a specified duration. Each machine can process at most one job at a time and once a job initiates processing on a given machine it must complete processing uninterrupted. A schedule is an assignment of operations to time slots on the machines. The objective of the JSP is to find a schedule that minimizes the maximum completion time, or makespan, of the jobs. In this paper, we describe a greedy randomized adaptive search procedure (GRASP) for the JSP. A GRASP is a metaheuristic for combinatorial optimization. Although GRASP is a general procedure, its basic concepts are customized for the problem being solved. We describe in detail our implementation of GRASP for job shop scheduling. Further, we incorporate to the conventional GRASP two new concepts: an intensification strategy and POP (Proximate Optimality Principle) in the construction phase. These two concepts were first proposed by Fleurent & Glover (1999) in the context of the quadratic assignment problem. Computational experience on a large set of standard test problems indicates that GRASP is a competitive algorithm for finding approximate solutions of the job shop scheduling problem. 1.
Production planning problems in printed circuit board assembly
, 2002
"... This survey describes some of the main optimization problems arising in the context of production planning for the assembly of printed circuit boards. The discussion is structured around a hierarchical decomposition of the planning process into distinct optimization subproblems, addressing issues su ..."
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Cited by 17 (0 self)
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This survey describes some of the main optimization problems arising in the context of production planning for the assembly of printed circuit boards. The discussion is structured around a hierarchical decomposition of the planning process into distinct optimization subproblems, addressing issues such as the assignment of board types to machine groups, the allocation of component feeders to individual machines, the determination of optimal production sequences, etc. The paper reviews the literature on this topic with an emphasis on the most recent developments, on the fundamental structure of the mathematical models and on the relation between these models and some ‘environmental’ variables such as the layout of the shop or the product
Efficient Methods for Scheduling MaketoOrder Assemblies under Resource, Assembly Area, and Part Availability Constraints
 International Journal of Production Research
, 1998
"... We consider the problem of scheduling multiple, largescale, maketoorder assemblies under resource, assembly area, and part availability constraints. Such problems typically occur in the assembly of high volume, discrete maketoorder products. Based on a list scheduling procedure which has b ..."
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Cited by 6 (1 self)
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We consider the problem of scheduling multiple, largescale, maketoorder assemblies under resource, assembly area, and part availability constraints. Such problems typically occur in the assembly of high volume, discrete maketoorder products. Based on a list scheduling procedure which has been proposed in Kolisch [19] we introduce three efficient heuristic solution methods. Namely, a biased random sampling method and two tabu searchbased largestep optimization methods. The two latter methods differ in the employed neighborhood. The first one uses a simple API neighborhood while the second one uses a more elaborated socalled `critical neighborhood ' which makes use of problem insight. All three procedures are assessed on a systematically generated set of test instances. The results indicate that especially the largestep optimization method with the critical neighborhood gives very good results which are significant better than simple singlepass list scheduling proce...
On the Importance of Sequencing Decisions in Production Planning and Scheduling
, 1999
"... We discuss the traditional hierarchical approach to production planning and scheduling, emphasizing the fact that scheduling constraints are often either ignored or considered in a very crude way. In particular, we point out that how sheduling is carried out is part of the capacity constraints on th ..."
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Cited by 4 (0 self)
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We discuss the traditional hierarchical approach to production planning and scheduling, emphasizing the fact that scheduling constraints are often either ignored or considered in a very crude way. In particular, we point out that how sheduling is carried out is part of the capacity constraints on the lotsizes. Usual methods to handle capacity in theory or in practice are reviewed. Finally, we present anapproach that tries to overcome these drawbacks by capturing the shopfloor capacity through scheduling considerations.
Techniques and Applications of Production Planning in Electronics Manufacturing Systems
, 1999
"... In this work we discuss production planning in electronics assemblyand, in particular, in PCB assembly. Our intention is to identify the typical problems arising from production planning and to give a survey of the solution methods suggested in the literature. In addition to this theoretical pers ..."
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Cited by 2 (2 self)
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In this work we discuss production planning in electronics assemblyand, in particular, in PCB assembly. Our intention is to identify the typical problems arising from production planning and to give a survey of the solution methods suggested in the literature. In addition to this theoretical perspective, we will briefly review applications designed for production planning in PCB assembly.
Constraint Programmin and GRASP Approaches to Schedule Oil Well Drillings
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GRASP Strategies for Scheduling Activities at Oil Wells with Resource Displacement
"... Before promising locations at petroliferous basins become productive oil wells, it is often necessary to complete drilling activities at these locations. The scheduling of such activities must satisfy several conflicting constraints and attain a number of goals. Moreover, resource displacements betw ..."
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Before promising locations at petroliferous basins become productive oil wells, it is often necessary to complete drilling activities at these locations. The scheduling of such activities must satisfy several conflicting constraints and attain a number of goals. Moreover, resource displacements between wells are also important. We describe a Greedy Randomized Adaptive Search Procedure (GRASP) for the scheduling of oil well development activities with resource displacement. The results are compared with schedules produced by a well accepted constraint programming implementation. Computational experience on real instances indicates that the GRASP implementation is