Shifting Bottleneck Procedure Research Articles

A note on the shifting bottleneck procedure for job shop scheduling

A note on the shifting bottleneck procedure for job shop scheduling

A shifting bottleneck procedure with multiple objectives in a complex manufacturing environment

Scheduling problems have been studied extensively over the years. Broad ranges of focus areas exist, from optimization to heuristics, production planning to production sequencing, customized algorithms to general-purpose algorithms, and from simple machines to complex environments. In this research, a heuristic approach has been proposed to overcome the scheduling problem on a complex job shop found at a manufacturer of commercial building products. The research is aimed at sequencing production orders in near-real-time, primarily to minimize total tardiness, but also to reduce total setup time. A layered Shifting Bottleneck Procedure is employed, with the top layer determining release dates and due dates for individual jobs, and the bottom layer applying algorithms to individual work centers. The outcome of this research is a better production schedule than current methods with minimal computation cost. The proposed framework performs well and could be applied to other production areas.

Hybrid algorithm based on improved extended shifting bottleneck procedure and GA for assembly job shop scheduling problem

With the makespan as the optimisation goal, we propose a hybrid solving method that combines improved extended shifting bottleneck procedure (i-ESB) and genetic algorithm (GA) for the assembly job shop scheduling problem (AJSSP). Hybrid genetic algorithm (HGA) uses a GA based on operation constraint chain coding to achieve global search and a local search based on an i-ESB. In the design of i-ESB, an extended disjunctive graph model (EDG) corresponding to AJSSP is presented. The calculation method of the operation head and tail length based on EDG is studied, as well as the searching method of key operations. The Schrage algorithm with disturbance is used to solve the single-machine scheduling subproblem. The selection criterion for bottleneck machines is increased. A greedy bottleneck machine re-optimisation process is designed. The effectiveness and superiority of the proposed algorithm are verified by testing and analysing the relevant examples in the literature.

A constructive heuristic for solving the Job-Shop Scheduling Problem

This work proposes the use of a constructive heuristic called Shifting Bottleneck Procedure for solving the Job-Shop Scheduling problem, with the aim to minimize the makespan, that is, the final delay of production planning. Because the constructive heuristic delivers an initial solution, then a Tabu Search method was used, with the aim to obtain a planification with the lowest possible makespan. The proposal was tested using benchmark data, and the results are promising, because the obtention of initial solutions using a constructive heuristic allows to decrease the processing time, and usually, the final results obtained from Tabu Search method are better.

An operational-level multi-stage mine production timetabling model for optimally synchronising drilling, blasting and excavating operations

This paper proposes a new multi-stage mine production timetabling (MMPT) model to optimise open-pit mine production operations including drilling, blasting and excavating under real-time mining constraints. The MMPT problem is formulated as a mixed integer programming model and can be optimally solved for small-size MMPT instances by IBM ILOG-CPLEX. Due to NP-hardness, an improved shifting bottleneck procedure algorithm based on the extended disjunctive graph is developed to solve large-size MMPT instances in an effective and efficient way. Extensive computational experiments are presented to validate the proposed algorithm that is able to efficiently obtain the near-optimal operational timetable of mining equipment units.

Configuration and the advantages of the shifting bottleneck procedure for optimizing the job shop total weighted tardiness scheduling problem

This paper answers two fundamental questions concerning the usage of the shifting bottleneck (SB) procedure to optimize the criterion total weighted tardiness for the classical job shop scheduling problem. The first question is how to configure the SB procedure, as it is a divide-and-conquer method and consists of diverse subsolutions for each procedure phase. The second question is what the advantages of the SB procedure are, in comparison with other state-of-the-art approaches. To answer the first question, we evaluate the performance (i.e. the scheduling quality) and the efficiency (i.e. the computational time) of various SB variants using computational experiments and present guidelines for configuring the SB procedure. To respond to the second question, extensive computational experiments were conducted on various benchmark instances (up to 100 jobs $$\times $$× 20 machines). Results show the superior performance/efficiency trade-off of the SB variants with certain configuration to local search methods. This excellent trade-off between performance and efficiency makes the SB procedure particularly promising for solving practical production scheduling problems.

A modified shifting bottleneck heuristic and disjunctive graph for job shop scheduling problems with transportation constraints

In this paper, we consider job shop scheduling problems with transportation constraints and bounded processing times. We use a modified disjunctive graph to represent the whole characteristics and constraints of such considered problems. Compared with classical disjunctive graph, it contains not only processing nodes, but also transportation and storage nodes. There are also positive and negative arcs for bounded processing time constraints, transportation times and minimum and maximum allowed storage times before and after each processing task. The objective is to minimise makespan. A feasible solution for makespan is found, if its associated graph contains no positive cycle. A modified shifting bottleneck procedure is used to solve the studied job shop problems which are represented by disjunctive graphs. It is coupled with a heuristic for assigning and sequencing transportation tasks iteratively. To validate our approach, several types of benchmarks with fixed or bounded processing times are tested, corresponding to flexible manufacturing systems, robotic cells and surface treatment facilities. Computational results show that the modified disjunctive graph and the proposed method are efficient and can deal with various cases.

Effective and efficient scheduling of dynamic job shops—Combining the shifting bottleneck procedure with variable neighbourhood search

Minimizing total weighted tardiness for job shops is a hard production scheduling problem. Shifting bottleneck (SB) procedures, which use a backtracking technique, can achieve excellent results for this problem. However, they usually require long computation times and do not scale well to larger problem instances of a realistic industrial size. In order to enhance the efficiency of SB procedures, we use variable neighbourhood search (VNS) instead of backtracking to optimize the machine planning sequence and the decomposed single machine problems. Evaluation on static benchmark problem instances and more realistic, dynamic scenarios confirms the performance and efficiency of our SB-VNS procedure.

A Modified Disjunctive Graph for Job-Shop Scheduling Problems with Bounded Processing Times and Transportation Constraints

Abstract In this paper, we propose a modified disjunctive graph to represent and help to address various types of job-shop problems with transport constraints. This graph contains positive and negative arcs for bounded processing times, and nodes for representation of processing tasks, transportation tasks and storage posts. Furthermore, solutions can be evaluated both by their makespan and by their total storage time for all operations if necessary. A modified shifting bottleneck procedure is used to solve the considered problems for minimizing makespan. To valid our approach, several types of benchmarks are tested, corresponding to flexible manufacturing systems and surface treatment facilities. Computational results show that the proposed graph and method are efficient and can deal with more general cases.

A hybrid shifting bottleneck procedure algorithm for the parallel-machine job-shop scheduling problem

In practice, parallel-machine job-shop scheduling (PMJSS) is very useful in the development of standard modelling approaches and generic solution techniques for many real-world scheduling problems. In this paper, based on the analysis of structural properties in an extended disjunctive graph model, a hybrid shifting bottleneck procedure (HSBP) algorithm combined with Tabu Search (TS) metaheuristic algorithm is developed to deal with the PMJSS problem. The original-version shifting bottleneck procedure (SBP) algorithm for the job-shop scheduling (JSS) has been significantly improved to solve the PMJSS problem with four novelties: (i) a topological-sequence algorithm is proposed to decompose the PMJSS problem in a set of single-machine scheduling (SMS) and/or parallel-machine scheduling subproblems; (ii) a modified Carlier algorithm based on the proposed lemmas and the proofs is developed to solve the SMS subproblem; (iii) the Jackson rule is extended to solve the PMS subproblem; (iv) a TS metaheuristic algorithm is embedded under the framework of SBP to optimise the JSS and PMJSS cases. The computational experiments show that the proposed HSBP is very efficient in solving the JSS and PMJSS problems.

An exact approach for single machine subproblems in shifting bottleneck procedures for job shops with total weighted tardiness objective

In this paper, we propose an exact solution method for single machine scheduling problems typically arising from bottleneck-based decomposition of weighted tardiness job shops. The encountered subproblems are characterized by delayed precedence constraints, multiple local due dates per operation and an objective function that is given by a weighted sum of maximum tardiness values. The key concept for solving these subproblems to optimality is a dominance rule whose underlying concepts have been newly developed to cope with the given structural properties. Furthermore, a simple lower bound and a dedicated constraint programming technique are presented. The efficiency of the proposed method is demonstrated by means of single machine problems collected during a run of a shifting bottleneck procedure for job shops in different size and due date tightness configurations.

Applying a hybrid job shop procedure to a Belgian manufacturing company producing industrial wheels and castors in rubber

In this paper, several methods for job shop scheduling are combined, adjusted and successfully applied to a real-world scheduling problem at a Belgian manufacturer producing industrial wheels and castors in rubber. The procedure is an extension of a hybrid shifting bottleneck procedure with a tabu search algorithm while incorporating various company specific constraints. The various extensions to cope with the company specific constraints have a strong similarity with the complex job shop problem formulation of Mason, Fowler, and Carlyle (2002). The new procedure is used as a simulation engine to test the relevance of various scenarios in order to improve the current planning approach of the company. A detailed computational experiment highlights the main contribution of the novel procedure for the company.

A two-stage hybrid memetic algorithm for multiobjective job shop scheduling

In this paper we address multiobjective job shop scheduling problems. After several decades of research in scheduling problems, a variety of heuristics have been developed. The proposed algorithm is a hybrid of three frequently applied ones: the dispatching rule, the shifting bottleneck procedure, and the evolutionary algorithm. It is a two-stage algorithm, which integrates a rule-based memetic algorithm in the first stage and a re-optimization procedure of shifting bottleneck in the second. We conduct experiments using benchmark instances found in the literature to assess the performance of the proposed method. The experimental results show that the proposed method is effective and efficient for multiobjective scheduling problems.

A disjunctive graph and shifting bottleneck heuristics for multi hoists scheduling problem

AbstractIn this paper, we studied a multi hoists scheduling problem with transportation constraints. For each job, there are several operations which can be operated on a set of machines (tanks), and their operation times are bounded. The transportation tasks are performed by several available transport resources. The objective is to determine an assignment of processing and transport resources and valid schedules on them without storage for both processing and transport operations while minimizing makespan. The assignments and schedules can be efficiently modeled by a disjunctive graph: negative arcs present the maximum processing and transportation times, and the length of the longest path without positive cycle represents the makespan of a feasible solution without storage. A modified genetic algorithm is used to do the assignment of tasks on resources. A modified Shifting Bottleneck procedure is applied to find a schedule for both machines’ and transports’ operations for a specific individual. Computational results for benchmark instances with several transport resources are presented.

A filter-and-fan approach to the job shop scheduling problem

The job shop scheduling problem (JSSP) is a notoriously difficult problem in combinatorial optimization. Extensive investigation has been devoted to developing efficient algorithms to find optimal or near-optimal solutions. This paper proposes a new heuristic algorithm for the JSSP that effectively combines the classical shifting bottleneck procedure (SBP) with a dynamic and adaptive neighborhood search procedure. Our new search method, based on a filter-and-fan (F&F) procedure, uses the SBP as a subroutine to generate a starting solution and to enhance the best schedules produced. The F&F approach is a local search procedure that generates compound moves by a strategically abbreviated form of tree search. Computational results carried out on a standard set of 43 benchmark problems show that our F&F algorithm performs more robustly and effectively than a number of leading metaheuristic algorithms and rivals the best of these algorithms.

Scheduling trains as a blocking parallel-machine job shop scheduling problem

In this paper, the train scheduling problem is modelled as a blocking parallel-machine job shop scheduling (BPMJSS) problem. In the model, trains, single-track sections and multiple-track sections, respectively, are synonymous with jobs, single machines and parallel machines, and an operation is regarded as the movement/traversal of a train across a section. Due to the lack of buffer space, the real-life case should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold the train until next section on the routing becomes available. Based on literature review and our analysis, it is very hard to find a feasible complete schedule directly for BPMJSS problems. Firstly, a parallel-machine job-shop-scheduling (PMJSS) problem is solved by an improved shifting bottleneck procedure (SBP) algorithm without considering blocking conditions. Inspired by the proposed SBP algorithm, feasibility satisfaction procedure (FSP) algorithm is developed to solve and analyse the BPMJSS problem, by an alternative graph model that is an extension of the classical disjunctive graph models. The proposed algorithms have been implemented and validated using real-world data from Queensland Rail. Sensitivity analysis has been applied by considering train length, upgrading track sections, increasing train speed and changing bottleneck sections. The outcomes show that the proposed methodology would be a very useful tool for the real-life train scheduling problems.

Modified bottleneck-based heuristic for large-scale job-shop scheduling problems with a single bottleneck

A modified bottleneck-based (MB) heuristic for large-scale job-shop scheduling problems with a welldefined bottleneck is suggested, which is simpler but more tailored than the shifting bottleneck (SB) procedure. In this algorithm, the bottleneck is first scheduled optimally while the non-bottleneck machines are subordinated around the solutions of the bottleneck schedule by some effective dispatching rules. Computational results indicate that the MB heuristic can achieve a better tradeoff between solution quality and computational time compared to SB procedure for medium-size problems. Furthermore, it can obtain a good solution in a short time for large-scale jobshop scheduling problems.

Ant colony optimization combined with taboo search for the job shop scheduling problem

In this paper, we present a hybrid algorithm combining ant colony optimization algorithm with the taboo search algorithm for the classical job shop scheduling problem. Instead of using the conventional construction approach to construct feasible schedules, the proposed ant colony optimization algorithm employs a novel decomposition method inspired by the shifting bottleneck procedure, and a mechanism of occasional reoptimizations of partial schedules. Besides, a taboo search algorithm is embedded to improve the solution quality. We run the proposed algorithm on 101 benchmark instances and obtain competitive results and a new best upper bound for one open benchmark instance is found.

IFORS' Operational Research Hall of Fame

International Transactions in Operational ResearchVolume 13, Issue 2 p. 169-174 Free Access IFORS' Operational Research Hall of Fame Egon Balas, Egon BalasSearch for more papers by this author Egon Balas, Egon BalasSearch for more papers by this author First published: 09 March 2006 https://doi.org/10.1111/j.1475-3995.2006.00541.xAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Selected Original Works Balas, E., 1965. An additive algorithm for solving linear programs with zero–one variables. Operations Research 13, 517– 546. Balas, E., 1969. Machine sequencing via disjunctive graphs: an implicit enumeration algorithm. Operations Research 17, 941– 957. Balas, E., 1970. Machine sequencing: disjunctive graphs and degree-constrained subgraphs. Naval Research Logistics Quarterly 17, 1– 9. Balas, E., 1974. Disjunctive programming: properties of the convex hull of feasible points. MSRR No. 348, Carnegie Mellon University, July. Also 1998. Discrete Applied Mathematics 89, 1– 44. Balas, E., 1989. The prize collecting traveling salesman problem. Networks 19, 621– 636. Balas, E., 1995. The prize collecting traveling salesman problem: II. Networks 25, 199– 216. Balas, E., Adams, J., Zawack, D., 1988. The shifting bottleneck procedure for job shop scheduling. Management Science 34, 391– 401. Balas, E., Ceria, S., Cornuéjols, G., 1993. A lift-and-project cutting plane algorithm for mixed 0–1 programs. Mathematical Programming 58, 295– 324. Balas, E., Fischetti, M., 1993. A lifting procedure for the asymmetric traveling salesman polytope and a large new class of facets. Mathematical Programming 58, 325– 352. Balas, E., Fischetti, M., 1999. Lifted cycle inequalities for the asymmetric traveling salesman problem. Mathematics of Operations Research 24, 273– 292. Balas, E., Fischetti, M., Pulleyblank, W.R., 1995. The precedence-constrained asymmetric traveling salesman polytope. Mathematical Programming 68, 241– 265. Balas, E., Pulleyblank, W.R., 1983. The perfectly matchable subgraph polytope of a bipartite graph. Networks 13, 495– 516. Balas, E., Vazacopoulos, A., 1998. Guided local search with shifting bottleneck for job shop scheduling. Management Science 44, 262– 275. Biographical Works Balas, E., 2000. Will to Freedom: A Perilous Journey through Fascism and Communism. Syracuse University Press, Syracuse, NY. Balas, E., 2002. Some thoughts on the development of integer programming during my research career. Lecture delivered upon receiving the EURO Gold Medal, July 9, 2001, Rotterdam. European Journal of Operational Research 141, 1– 7. Volume13, Issue2March 2006Pages 169-174 ReferencesRelatedInformation

Applying the fuzzy ranking method to the shifting bottleneck procedure to solve scheduling problems of uncertainty

Because the impreciseness of processing time is popular in the real world, this research proposes a procedure to combine the fuzzy ranking method and the shifting bottleneck procedure (SB) to solve scheduling problems. The SB is explained here and the needed formulations to transfer fuzzy numbers into crisp numbers are provided with its proofs. A numeric example is particularly provided to explain the proposed procedure in detail. The results show that the procedure is useful for it can be utilized not only in fuzzy type problems but also in crisp type problems.