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A disjunctive graph modeling a mixed shop for hybrid flowshop scheduling, with processing times t i j k at nodes O i j k for N (=3) jobs on S (=3) stages, with respectively Q 1 =2 (hybrid), Q 2 =1, Q 3 =1 resources. Colored disjunctive arcs represent the candidate resource for the connected nodes (operations). Bottom: the top digraph partially transformed in acyclic digraph by directing disjunctive arcs on two paths starting from node 0 and ending at node * (green and brown) and one ending in O 222 (yellow).
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The proposed hybrid stage shop scheduling (HSSS) model, inspired from a real case in the high-fashion industry, aims to fully exploit the potential of parallel resources, splitting and overlapping concurrent operations among teams of multifunctional machines and operators on the same job.
The HSSS formally extends mixed shop scheduling (a combinati...
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Citations
... On the other hand, for flexible job shop problems mathematical programming still plays a relevant role in finding the optimal routing. In this direction, disjunctive graphs in combination with Mixed Integer Linear Programming (MILP) have been proposed to minimize the makespan [8]. Deep reinforcement learning was revealed to be promising too for short-term scheduling [9], while in [10] Petri Nets and a heuristic based on artificial intelligence have been combined to solve flexible manufacturing systems scheduling problems. ...
... Then, compared the results to the basic ABC and a new Covariance Matrix Adaptation Evolutionary Strategy algorithm (CMA-ES). In Rossi et al. (2015) an extension of the mixed shop problem, that is a hybrid stage shop was proposed which was inspired by a real industrial case. ...
Stage shop scheduling is a type of manufacturing problem, in which operations need to be done on a group of jobs and are separated into different phases depending on their types. The stages are carried out in a sequential order; however, the operations within each stage are carried out in any order. In other words, the operations of a stage cannot be initiated until all operations of the previous stage are completed. Human-robot collaboration has become more popular as technologies and business empowerment has brought humans and robots closer together. In this study, jobs are allocated to humans and robots by presenting a bi-objective linear model to minimize the makespan and the cost of utilizing agents in a stage shop problem. Moreover, an interactive method is used to convert the model into a single objective one. The sensitivity results show that the makespan is minimized noticeably by collaborating the human and robots.
... The Hybrid Stage Shop Scheduling (HSSS) which formally encompasses diverse shop scheduling (a combination of flowshop and open shop), can model routing flexibility, and hybrid shop scheduling to established the resource flexibility. The HSSS is proposed in [20]. The proposed model integrates group shop scheduling and process planning. ...
Flexible flow shop is becoming more interested and applied in industries due to its impact from higher workloads. Flexible flow shop scheduling problem is focused to minimize the makespan. A metaheuristic model based on Hybrid Tabu Search is developed to overcome this problem. Firstly, Hybrid Tabu Search is modelled based on the factory data. The Earliest Due Date rule is used as the scheduling method for the current status. FlexSim simulation software is used to evaluate the Hybrid Tabu Search model. The outcome is validated with two different basic heuristic solutions; Campbell, Dudek and Smith’s and Gupta’s heuristics. It is found that the proposed model can improve the job sequence based on makespan criteria.
... Nasiri [11] proposed a modified artificial bee colony (ABC) algorithm to solve the stage shop scheduling problem and compared the results with the basic ABC and a new algorithm called evolution strategy with covariance matrix adaptation (CMA-ES). Inspiring from a real industrial case, another extension of the mixed shop problem called the hybrid stage shop was proposed by Rossi, Soldani [12]. Jin, Tang [13] developed several novel mixed integer linear programming models for the scheduling of a job shop flexible manufacturing system. ...
Remarkable efforts are made to develop the job shop scheduling problem up to now. As a novel generalization, the stage shop can be defined as an environment, in which each job is composed of some stages and each stage may include one operation or more. A stage can be defined a subset of operations of a job, such that these operations can be done in any arbitrary relative order while the stages should be processed in a predetermined order. In other words, the operations of a stage cannot be initiated until all operations of the prior stage are completed. In this paper, an innovative lower bound based on solving the preemptive open shop (using a linear programming model in polynomial time) is devised for the makespan in a stage shop problem. In addition, three metaheuristics, including firefly, harmony search and water wave optimization algorithms are applied to the problem. The results of the algorithms are compared with each other, the proposed lower bound, and a commercial solver.
... General flow shop has only one machine per stage and the flow of the jobs must be in the given order of stages. According to Rossi, Soldani and Lanzetta (2015), the sequence of operations in flow shop for each of the job (routing) is linear and predefined. Basically, regular flow-shop problem has two components; a) a group of M machines b) a set of N jobs to be executed on this group of machine. ...
To face the challenges of industrial globalization and sustain in the competitive market, the manufacturers have to gratify the customer demand by launching the products on time having variable design and volume at low price. In this regards, the necessity of adopting the epitome of flexible mass production flow shop structure along with the appropriate production planning tools and techniques like scheduling knows no bound. As a consequence, numerous approaches have already proposed for scheduling the production flow shop. However, before the adoption of any of these conventional approaches it is an utmost need for the manufacturer to realize its consequences and the appropriateness. Therefore, in this endeavour, we anticipated mixed integer linear-programming model for machine scheduling in flow shop environment based on multi-machine and multi-product scenario. Real data from industry has been collected by conducting several site visits at a local production system. The model then was analysed using What's Best Excel Solver. The result shown by adopting the appropriate sequence, it is possible to achieve the minimum completion time compared to other possible sequence combination of products. By minimizing the makespan, the idle times of some of the machine will be reduced meanwhile the utilization of the machine will be maximized consequently.
... Zhang et al. [94] also used meta-heuristics to solve the problem of minimizing a function composed of production costs and tardiness in a car plant. Rossi et al. [68] developed a MILP model and constructive heuristics for a high-fashion industry.Gedik et al. [27] proposed a constraint programming model and logic-based Benders algorithms to optimize the inland waterway infrastructure maintenance operations conducted by the U.S. Army Corps of Engineers. They take into account constraints such as environmental windows, dredge resource cost and availability, and sequence dependent travel times. ...
The problems of production scheduling and sequencing refer to decision making regarding the designation of jobs to available resources and their subsequent order to optimize pre-defined performance measures. From the early days of research in this area until this last decade, the publication of case studies has been scarce, with their frequency only increasing very recently. This survey aims to highlight practical research and case studies published in the literature in the scheduling area, identifying the main characteristics of the problems treated, trends in this research and also gaps showing potential areas for future study.
... With the introduction of the concept of industrial Internet, the processing of products in the traditional manufacturing industry has become more complex. As a result, a variety of complex flow shop scheduling models have emerged, such as nonsmooth FSP ( Ferrer, Guimarans, Ramalhinho, & Juan, 2016 ), non-permutation FSP ( Mehravaran & Logendran, 2013 ), mixed-blocking FSP ( Riahi, Khorramizadeh, Newton, & Sattar, 2017 ) and hybridstage-shop-scheduling ( Rossi, Soldani, & Lanzetta, 2015 ). FSP has been extended to many branches: permutation FSP (PFSP) ( Shao & Pi, 2016 ;Zhao, Zhang, Wang, & Zhang, 2015 ), no-wait FSP (NWFSP), blocking FSP (BFSP) ( Fernandez-Viagas, Leisten, & Framinan, 2016 ), no-idle FSP (NIFSP) ( Shao, Pi, & Shao, 2017 ), flexible Flow Shop ( Shahvari, Salmasi, Logendran, & Abbasi, 2012 ), FSP with buffers ( Zhao, Tang, Wang, & Jonrinaldi, 2014 ) and hybrid FSP (HFSP) ( Bozorgirad & Logendran, 2013;Shahvari & Logendran, 2016 ), etc. ...
In this paper, a discrete Water Wave Optimization algorithm (DWWO) is proposed to solve the no-wait flowshop scheduling problem (NWFSP) with respect to the makespan criterion. Inspired by the shallow water wave theory, the original Water Wave Optimization (WWO) is constructed for global optimization problems with propagation, refraction and breaking operators. The operators to adapt to the combinatorial optimization problems are redefined. A dynamic iterated greedy algorithm with a changing removing size is employed as the propagation operator to enhance the exploration ability. In refraction operator, a crossover strategy is employed by DWWO to avoid the algorithm falling into local optima. To improve the exploitation ability of local search, an insertion-based local search scheme which is utilized as breaking operator, is applied to search for a better solution around the current optimal solution. A ruling out inferior solution operator is also introduced to improve the convergence speed. The global convergence performance of the DWWO is analyzed with the Markov model. In addition, the computational results based on well-known benchmarks and statistical performance comparisons are presented. Experimental results demonstrate the effectiveness and efficiency of the proposed DWWO algorithm for solving NWFSP.
... Hutchinson and Pflughoeft (1994) consider general flexible process plans. Rossi et al. (2015) include routing and resource flexibility in a mixed-shop setting that combines flow-shop and open-shop problems. Barták andČepek (2008) consider nested precedence networks with alternatives. ...
The integration of batching machines within a job-shop environment leads to a complex job-shop scheduling problem. Semiconductor manufacturing presumably represents one of the most prominent practical applications for such problems. We consider a flexible job-shop scheduling problem with p-batching, reentrant flows, sequence dependent setup times and release dates while considering different regular objective functions. The scheduling of parallel batching machines and variants of the job-shop scheduling problem are well-studied problems whereas their combination is rarely considered.Existing disjunctive graph approaches for this combined problem rely on dedicated nodes to explicitly represent batches. To facilitate modifications of the graph, our new modeling reduces this complexity by encoding batching decisions into edge weights. An important contribution is an original algorithm that takes batching decisions “on the fly” during graph traversals. This algorithm is complemented by an integrated move to resequence and reassign operations. This combination yields a rich neighborhood that we apply within a GRASP based metaheuristic approach.We extend this approach by taking further constraints into account that are important in the considered industrial application. In particular, we model internal resources of machines in detail and take maximum time lag constraints into account. Numerical results for benchmark instances of different problem types show the generality and applicability of our approach. The conciseness of our idea facilitates extensions towards further complex constraints needed in real-world applications.
... The decomposition of operations into suboperations may produce better scheduling, unless the uncertainty or high dispersion of actual times frustrates the intent. The composition/decomposition of operations and the connections between planning and scheduling with exible (manual) resources were developed in Rossi, Soldani, and Lanzetta (2015). ...
Uncertain (manual) activity times impact a number of manufacturing system modules: plant and layout design, capacity analysis, operator assignment, process planning, scheduling and simulation. Direct observation cannot be used for non-existent production lines. A hybrid direct observation/synthetic method derived from Method Time Measurement available in industry is proposed. To determine accurate activity times required by heuristics and metaheuristics optimisation, manufacturing system modules are modelled by MILP and operator efficiency parameters are used for time standardisation. Among human factors considered are skill and ergonomics. Application to the sterilisation of reusable medical devices is extensively described. Experimental data taken from observation on the field and a worst-case date have shown the model direct applicability for professionals also to non-manufacturing cases.
... Although it is beneficial for lead-time reduction, operation overlapping also requires additional costs for rework. An analytical model has also been developed to improve the project performance by balancing its negative and positive effects [16]. ...
Sustainable supply chain management (SSCM) has appeared to be important in business practices in order to survive in the competition. Sustainable performance assessment, that includes economic, social, and environmental aspects need to be given due attention by the business players in order to understand the position of the company so that it can fulfill customer satisfaction. In this research, each of the aspects is measured using different methods. The Economic performance assessment is represented using the Supply Chain Operation Reference (SCOR) model that helps in measuring the success of a supply chain operation. It uses 15 indicators deemed relevant in the Make-to-Stock production typology that is distributed into five performance attributes. The economic assessment is then obtained through these performance attributes that result in 97.5% in agility, 92% in cost, 78.2% in reliability, 72% in asset management, and 40.67% in responsiveness. Meanwhile, the social performance assessment is directed at employee's welfare. Questionnaires are distributed to 30 employees to measure company's commitment to address their social issues. It results in a perfect score as 100% in fair salary, annual allowance, and training, while health insurance and safety equipment only cover 70% and 30%, respectively. The environmental aspect is noticed on the wastewater management, since it mainly contributes for company's waste. The assessment lies on the liquid contamination test and is compared to the maximum standard level, set by the government. Environmental assessment shows 76.8% in acidity, 71.93% in Biological Oxygen Demand (BOD), 33.15% in temperature, and 0% in both Total Suspended Solid (TSS) and Chemical Oxygen Demand (COD). While this research is focusing on improving the performance in the supply chain process (Economic aspect), which is the worst assessment in the economic aspect, which is responsiveness, it is selected to be improved to reach an optimum performance. Therefore, the operation-overlapping approach is applied in the scheduling of the production process to improve company’s responsiveness, which is from 40.67% to 60.67%.
