2014
DOI: 10.1007/s10951-014-0395-8
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Metaheuristics for a scheduling problem with rejection and tardiness penalties

Abstract: In this paper, we consider a single-machine scheduling problem (P) inspired from manufacturing instances. A release date, a deadline, and a regular (i.e., non-decreasing) cost function are associated with each job. The problem takes into account sequence-dependent setup times and setup costs between jobs of different families. Moreover, the company has the possibility to reject some jobs/orders, in which case a penalty (abandon cost) is incurred. Therefore, the problem at hand can be viewed as an order accepta… Show more

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Cited by 34 publications
(13 citation statements)
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References 39 publications
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“…In any case, heuristic algorithms are needed to deal with real-life instances of the slot scheduling problem at network level. Heuristic algorithms that have been successfully applied in resource-constrained scheduling problems include: (i) Tabu Search algorithms (Thevenin et al 2015), (ii) evolutionary algorithms (Datta et al 2008) and (iii) Ant Colony optimisation algorithms (Castelli et al 2011). …”
Section: Network-based Slot Schedulingmentioning
confidence: 99%
“…In any case, heuristic algorithms are needed to deal with real-life instances of the slot scheduling problem at network level. Heuristic algorithms that have been successfully applied in resource-constrained scheduling problems include: (i) Tabu Search algorithms (Thevenin et al 2015), (ii) evolutionary algorithms (Datta et al 2008) and (iii) Ant Colony optimisation algorithms (Castelli et al 2011). …”
Section: Network-based Slot Schedulingmentioning
confidence: 99%
“…). As described in [39], a local search starts from an initial solution and then explores the solution space by moving from the current solution to a neighbor solution. A neighbor solution is usually obtained by making a slight modification of the current solution, called a move.…”
Section: Decent Local Search Heuristics (mentioning
confidence: 99%
“…Numerous periodic and continuous inventory review models have been proposed to optimize echelon's cost and profit, and consequently to improve supply chain performance (e.g., Aviv, 2002;Clark and Scarf, 1960;De Bodt and Graves, 1985;Federgruen and Zipkin, 1984;Silver and Zufferey, 2011). Some works have also proposed to improve the global performance of a supply chain when focusing on the improvement of: the production level only (Thevenin et al, 2015(Thevenin et al, , 2016; the quality management and the value chain (Voldrich et al, 2017); the inventory dispatching when facing unreliable suppliers (Respen et al, 2017); the design of the supply chain itself (Carle et al, 2012). However, the actual behavior shows that decision maker's mind has a restricted capacity to formulate complex problems in a finite time, based on the available information (e.g., Loch and Wu, 2007;Gino and Pisano, 2008;Simon, 1969).…”
Section: Introductionmentioning
confidence: 99%