Heuristic and Exact Algorithms for the Two-Machine Just in Time Job Shop Scheduling Problem

The problem addressed in this paper is the two-machine job shop scheduling problem when the objective is to minimize the total earliness and tardiness from a common due date (CDD) for a set of jobs when their weights equal 1 (unweighted problem). This objective became very significant after the introduction of the Just in Time manufacturing approach. A procedure to determine whether the CDD is restricted or unrestricted is developed and a semirestricted CDD is defined. Algorithms are introduced to find the optimal solution when the CDD is unrestricted and semirestricted. When the CDD is restricted, which is a much harder problem, a heuristic algorithms proposed to find approximate solutions. Through computational experiments, the heuristic algorithms\u27 performance is evaluated with problems up to 500 jobs

Hardware Implementation of a Mamdani Fuzzy Logic Controller for a Static Compensator in a Multimachine Power System

A Mamdani-type fuzzy logic controller is designed and implemented in hardware for controlling a static compensator (STATCOM), which is connected to a ten-bus multimachine power system. Such a controller does not need any mathematical model of the plant to be controlled and can efficiently provide control signals for the STATCOM over a wide range of operating conditions of the power system and during different disturbances. The proposed controller is implemented using the M67 digital signal processor board and is interfaced to the multimachine power system simulated on a real-time digital simulator. Experimental results are provided, showing that the proposed Mamdani fuzzy logic controller provides superior damping compared to the conventional proportional-integral (PI) controller for both small and large scale disturbances. In addition, the proposed controller manages to restore the power system to the steady state conditions with less control effort exerted by the STATCOM, which, in turn, leads to smaller megavar rating and, therefore, less cost for the device. The matrix pencil method analysis of the damping provided by the different controllers indicates that the proposed controller provides higher damping than the PI controller and also mitigates the modes present with the conventional PI control

Minimizing makespan of multimachine production system in flow shop environment by means of mixed integer programming model

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

A search method for optimal control of a flow shop system of traditional machines

Cataloged from PDF version of article.We consider a convex and nondifferentiable optimization problem for deterministic flow shop systems in which the arrival times of the jobs are known and jobs are processed in the order they arrive. The decision variables are the service times that are to be set only once before processing the first job, and cannot be altered between processes. The cost objective is the sum of regular costs on job completion times and service costs inversely proportional to the controllable service times. A finite set of subproblems, which can be solved by trust-region methods, are defined and their solutions are related to the optimal solution of the optimization problem under consideration. Exploiting these relationships, we introduce a twophase search method which converges in a finite number of iterations. A numerical study is held to demonstrate the solution performance of the search method compared to a subgradient method proposed in earlier work. 2010 Elsevier B.V. All rights reserved

Comparison of a bat and genetic algorithm generated sequence against lead through programming when assembling a PCB using a 6 axis robot with multiple motions and speeds

An optimal component feeder arrangement and robotic placement sequence are both important for improving assembly efficiency. Both problems are combinatorial in nature and known to be NP-hard. This paper presents a novel discrete hybrid bat-inspired algorithm for solving the feeder slot assignment and placement sequence problem encountered when planning robotic assembly of electronic components. In our method, we use the concepts of swap operators and swap sequence to redefine position, and velocity operators from the basic bat algorithm. Furthermore, we propose an improved local search method based on genetic operators of crossover and mutation enhanced by the 2-opt search procedure. The algorithm is formulated with the objective of minimizing the total traveling distance of the pick and place device. Through numerical experiments, using a real PCB assembly scenario, we demonstrate the considerable effectiveness of the proposed discrete Bat Algorithm (BA) to improve selection of feeder arrangement and placement sequence in PCB assembly operations and achieve high throughput production. The results also highlighted that the even though the algorithms out performed traditional lead through programming techniques, the programmer must consider the influence of different robot motions

Allocation of component types to machines in the automated assembly of printed circuit boards

Duman, Ekrem (Dogus Author) -- An earlier version of this paper which has been presented at ISCIS'06: The 21st International Symposium on Computer and Information Sciences, November 1-3, 2006 Istanbul, Turkey, has been published in Lecture Notes in Computer Science [18].Although the use of electronic component placement machines has brought reliability and speed to the printed circuit board (PCB) assembly process, to get higher utilization, one needs to solve the resulting complex operations research problems efficiently. In this study, the problem of distributing the assembly workload to two machines deployed on an assembly line with two identical component placement machines to minimize the line idle time is considered. This problem is NP-Complete even in its simplest form. A mathematical model and several heuristics have been proposed to solve this problem efficiently

Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs

In many real scheduling environments, a job processed later needs longer time than the same job when it starts earlier. This phenomenon is known as scheduling with deteriorating jobs to many industrial applications. In this paper, we study a scheduling problem of minimizing the total completion time on identical parallel machines where the processing time of a job is a step function of its starting time and a deteriorating date that is individual to all jobs. Firstly, a mixed integer programming model is presented for the problem. And then, a modified weight-combination search algorithm and a variable neighborhood search are employed to yield optimal or near-optimal schedule. To evaluate the performance of the proposed algorithms, computational experiments are performed on randomly generated test instances. Finally, computational results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time even for large-sized problems