Gündüz Ulusoy

A survey on the resource-constrained project scheduling problem

In this paper, research on the resource-constrained project scheduling problem is classified according to specified objectives and constraints. Each classified area is extensively surveyed, and special emphasis is given to trends in recent research. Specific papers involving nonrenewable resource constraints and time/cost-based objectives are discussed in detail because they present models that are close representations of real-world problems. The difficulty of solving such complex models by optimization techniques is noted. For the purposes of this survey, a set of 78 optimally solved test problems from the literature and a second set of 110 benchmark problems have been subjected to analysis with some well-known dispatching rules and a scheduling algorithm that consists of a decision-making process utilizing the problem constraints as a base of selection. The computational results are reported and discussed in the text. Constructive scheduling algorithms that are directly based on the problem constraints...

Organizational Support for Intrapreneurship and its Interaction with Human Capital To Enhance Innovative Performance

Purpose – The main purpose of this paper is to investigate the direct and interactive effects of organizational support and human capital on the innovative performance of companies. Individual effects of the organizational support dimensions, namely: management support for generating and developing new business ideas, allocation of free time, convenient organizational structures concerning, in particular, decentralization level or decision-making autonomy, appropriate use of incentives and rewards, and tolerance for trial-and-errors or failures in cases of creative undertakings or risky project implementations, are also to be investigated.Design/Methodology/Approach – The study develops and tests a theoretical research model where the organizational support dimensions are the independent variables, innovative performance is the dependent variable, and the human capital has a moderating role in this relationship, via a questionnaire study covering 184 manufacturing firms in Turkey.Findings – Among the individual direct effects of the dimensions of organizational support, management support for idea development and tolerance for risk taking are found to exert positive effects on innovative performance. Availability of a performance based reward system and free time have no impact on innovativeness, while work discretion has a negative one. As for the role of human capital (HC), it is found to be an important driver of innovative performance especially when the OS is limited. However, when the levels of both HC and OS are high, innovative performance does not increase any further.Originality/Value – Two distinct research streams, namely organizational support literature and human capital literature, have already focused on their individual impacts on the innovative performance. However, a combination of these separate streams was not tried before. The paper discusses and investigates what will happen when both positive drivers interact with each other. Moreover, it also investigates how organizational support and human capital are complementary.

Parallel machine scheduling with earliness and tardiness penalties

Abstract In the parallel machine scheduling problem with earliness and tardiness penalties (PMSP_E/T) considered here, a set of independent jobs with sequence-dependent setups is given to be scheduled on a set of parallel machines (processors) in a non-preemptive fashion such that the sum of the weighted earliness and tardiness values of all jobs is minimized. The due dates of the jobs are distinct which complicates the problem. In addition, each job has its own arrival time which brings the model closer to reality but complicates it further. The weights for earliness and tardiness are common to all jobs and are unequal in general. Two genetic algorithm approaches are employed to attack this problem; one with a crossover operator which is developed to solve multi-component combinatorial optimization problems of which PMSP_E/T is an instance, and the other with no crossover operator. Results of tests on 960 randomly generated problems indicate that genetic algorithms provide an efficient algorithm for PMSP_E/T; that neighborhood exchange type of search can yield relatively better results in small and easy instances of the problem but the genetic algorithm with the crossover operator outperforms such search in larger-sized, more difficult problems; and that the recombinative power of the genetic algorithm with the crossover operator improves with increasing problem size and difficulty making it ever more attractive for applications of larger sizes. Scope and purpose The parallel machine scheduling problem is an important and difficult problem. Traditionally, the problem has consisted of scheduling of a set of independent jobs on identical parallel machines (processors) with the aim of minimizing maximum job completion. In line with current trends towards just-in-time manufacturing strategies, where both early and tardy finishing of job processing are undesired, objectives related to earliness and tardiness penalties have become increasingly popular. Yet, already the scheduling of independent jobs with a common due date on a single machine is an NP-hard problem. Research efforts have therefore concentrated on heuristic approaches. This paper presents one such approach. Genetic algorithms (GAs) have become very popular as search algorithms due to their effectiveness and efficiency in large and complex search spaces. In this study, a genetic algorithm approach is developed to attack the problem of scheduling of a set of independent jobs on parallel machines. To model the actual practice more closely, assumptions such as distinct due dates and arrival times for jobs, different processing rates for machines and sequence-dependent set-up times are incorporated into the problem formulation. To the best knowledge of the authors, parallel machine scheduling problems of this scope have not been treated in the literature before. Computational results on a large test bed illustrate the effectiveness of GAs on this problem in general and the potentials of GAs with a new crossover operator (MCUOX – multi-component uniform order-based crossover) for problems of increasing sizes and difficulty.

A genetic algorithm approach to the simultaneous scheduling of machines and automated guided vehicles

Abstract This article addresses the problem of simultaneous scheduling of machines and a number of identical automated guided vehicles (AGVs) in a flexible manufacturing system (FMS) so as t minimize the makespan. For solving this problem, a genetic algorithm (GA) is proposed. Here, chromosomes represent both operation sequencing and AGV assignment dimensions of the search space. A third dimension, time, is implicitly given by the ordering of operations of the chromosomes. A special uniform crossover operator is developed which produces one offspring from two parent chromosomes. It transfers any patterns of operation sequences and/or AGV assignments that are present in both parents to the child. Two mutation operators are introduced; a bitwise mutation for AGV assignments and a swap mutation for operations. Any precedence infeasibility resulting from the operation swap mutation is removed by a repair function. The schedule associated with a given chromosome is determined by a simple schedule builder. After a number of problems are solved to evaluate various search strategies and to tune the parameters of the proposed GA, 180 test problems are solved to evaluate various search lower bound is introduced and compared with the results of GA. In 60% of the problems GA reaches the lower bound indicating optimality. The average deviation from the lower bound over all problems is found to be 2.53%. Additional comparison is made with the time window approach suggested for this same problem using 82 test problems from the literature. In 59% of the problems GA outperforms the time window approach where the reverse is true only in 6% of the problems.

A Time Window Approach to Simultaneous Scheduling of Machines and Material Handling System in an FMS

This paper exploits the interactions between the machine scheduling and the scheduling of the material handling system in an FMS by addressing them simultaneously. The material transfer between machines is done by a number of identical automated guided vehicles (AGVs) which are not allowed to return to the load/unload station after each delivery. This operating policy introduces an additional complexity to the problem because it results in sequence-dependent travel times for the deadheading trips between successive loaded trips of the AGVs. The problem is formulated as a nonlinear mixed integer programming model. Its objective is makespan minimization. The formulation consists of constraint sets of a machine scheduling subproblem and a vehicle scheduling subproblem which interact through a set of time window constraints for the material handling trip starting times. An iterative procedure is developed where, at each iteration, a new machine schedule is generated by a heuristic procedure, the operation completion times obtained from this schedule are used to construct time windows for the trips, and a feasible solution is searched for the second subproblem, which is handled as a sliding time window problem. The procedure is numerically tested on 90 example problems.

The fleet size and mix problem for capacitated arc routing

Abstract There have been several attempts to solve the capacitated arc routing problem with m vehicles starting their tours from a central node. The objective has been to minimize the total distance travelled. In the problem treated here we also have the fixed costs of the vehicles included in the objective function. A set of vehicle capacities with their respective costs are used. Thus the objective function becomes a combination of fixed and variable costs. The solution procedure consists of four phases. In the first phase, a Chinese or rural postman problem is solved depending on whether all or some of the arcs in the network demand service with the objective of minimizing the total distance travelled. It results in a tour called the giant tour. In the second phase, the giant tour is partitioned into single vehicle subtours feasible with respect to the constraints. A new network is constructed with the node set corresponding to the arcs of the giant tour and with the arc set consisting of the subtours of the giant tour. The arc costs include both the fixed and variable costs of the subtours. The third phase consists of solving the shortest path problem on this new network to result in the least cost set of subtours represented on the new network. In the last phase a postprocessor is applied to the solution to improve it. The procedure is repeated for different giant tours to improve the final solution. The problem is extended to the case where there can be upper bounds on the number of vehicles with given capacities using a branch and bound method. Extension to directed networks is given. Some computational results are reported.

Multiprocessor task scheduling in multistage hybrid flow-shops: a genetic algorithm approach

This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment. The objective is to minimize the make-span, that is, the completion time of all the tasks in the last stage. This problem is of practical interest in the textile and process industries. A genetic algorithm (GA) is developed to solve the problem. The GA is tested against a lower bound from the literature as well as against heuristic rules on a test bed comprising 400 problems with up to 100 jobs, 10 stages, and with up to five processors on each stage. For small problems, solutions found by the GA are compared to optimal solutions, which are obtained by total enumeration. For larger problems, optimum solutions are estimated by a statistical prediction technique. Computational results show that the GA is both effective and efficient for the current problem. Test problems are provided in a web site at www.benchmark.ibu.edu.tr/mpt-hfsp.

An assessment of supply chain and innovation management practices in the manufacturing industries in Turkey

This paper aims at assessing the supply chain and innovation management in the manufacturing industries in Turkey on an empirical basis. The assessments presented are based on parts of the data and information collected through the execution of the Competitive Strategies and Best Practices Benchmarking Questionnaire in 82 companies from four sectors of the manufacturing industries in Turkey. Results of these sectoral benchmarking studies reported elsewhere indicate the need of adopting product differentiation particularly through more knowledge intensive products as the dominant competitive strategy and also the need for improvement in various areas of supply chain as well as innovation management. In this paper, these issues are analysed through the survey results and some conclusions are drawn. Several policy measures applicable in near future are suggested for improving the areas found in need of improvement.

A local constraint based analysis approach to project scheduling under general resource constraints

Abstract In the doubly-constrained project scheduling problem where nonrenewable resources are constrained both on a period and a project basis, the combinatorial complexity arising from interrelated precedence, renewable and nonrenewable resource constraints necessitates a solution approach which takes all such considerations into account including the objectives. In this context an activity is permitted to operate in one of its modes, each of which represents the trade off between different choices of resource requirements (types) and operating durations. The proposed heuristic approach to handle this problem is local constraint based analysis (LCBA) where the selection of activities and their respective modes is made locally at every decision point. LCBA imposes precedence relationships on activities which guarantee the feasibility of the current makespan constrained by the available resource levels at that decision point as long as a complete sequence of schedulable activities is found. The procedure is also adapted to various model extensions such as flexible resource requirement levels. The procedure can also be utilized in a dynamic environment where resource absenteeism, activity duration changes and readjustment of the project network configuration are accounted for. Numerical results are obtained for LCBA and three well-reputed dispatching rules to show that considerably better solutions are obtained by the LCBA approach in encouragingly short computation times.

Four Payment Models for the Multi-Mode Resource Constrained Project Scheduling Problem with Discounted Cash Flows

In this paper, the multi-mode resource constrained project scheduling problem with discounted cash flows is considered. The objective is the maximization of the net present value of all cash flows. Time value of money is taken into consideration, and cash in- and out-flows are associated with activities and/or events. The resources can be of renewable, nonrenewable, and doubly constrained resource types. Four payment models are considered: lump sum payment at the terminal event, payments at prespecified event nodes, payments at prespecified time points and progress payments. For finding solutions to problems proposed, a genetic algorithm (GA) approach is employed, which uses a special crossover operator that can exploit the multi-component nature of the problem. The models are investigated at the hand of an example problem. Sensitivity analyses are performed over the mark up and the discount rate. A set of 93 problems from literature are solved under the four different payment models and resource type combinations with the GA approach employed resulting in satisfactory computation times. The GA approach is compared with a domain specific heuristic for the lump sum payment case with renewable resources and is shown to outperform it.