European J. of Industrial Engineering (14 papers in press)
Effects of human errors and trade-credit financing in two-echelon supply chain models
by Dongmin Shin, Mandeep Mittal, Biswajit Sarkar
A decomposition heuristic for short-term planning of assessment centres
by Tom Rihm, Norbert Trautmann
Abstract: In an assessment centre, several candidates for a job vacancy perform a set of predefined tasks while being observed and evaluated by so-called assessors. For the organizers of such assessment centres, a challenging job is to schedule the tasks and assign the prescribed number of assessors to the tasks such that the total waiting time for the assessors is minimized. This planning situation has been reported to us by a human resource management service provider. Application-specific restrictions distinguish this problem from related scheduling problems discussed in the literature, e.g., the resource-constrained project scheduling problem. We present a mixed-integer-programming-based decomposition heuristic, which iterates between pre-scheduling, assignment, and re-scheduling subproblems. Our computational results demonstrate that this novel heuristic outperforms the state-of-the-art approaches on a set of 240 benchmark instances. Furthermore, this heuristic provides optimal solutions to a set of four real-life instances.
Keywords: OR in the service industries; human resource management; assessment centre; project scheduling; decomposition heuristic; MIP; mixed-integer programming.
A mixed-integer programming-based heuristic for project scheduling with work-content constraints
by Adrian Zimmermann
Abstract: We consider the project scheduling problem in which each project activity has a prescribed work content that must be completed by a so-called work-content resource and the activities' resource usage may change over time. The resource usage must lie within prescribed bounds and cannot be changed for a minimum number of consecutive periods. The amount of resource units used determines the requirements for further resources. The activities must be scheduled such that the project makespan is minimized. For this problem, we devise a mixed-integer programming-based heuristic that schedules the activities iteratively. To improve the resource usage for multiple activities simultaneously, subsets of activities are rescheduled each time the activities' resource usage appears to be inefficient. Our computational results for a standard test set from the literature show that our heuristic outperforms the state-of-the-art method for medium- and large-sized instances, and that for many small-sized instances, optimal solutions are obtained.
Keywords: MIP-based heuristic; mixed-integer linear programming; project scheduling; flexible resource usage; work content.
An Adaptive Large Neighborhood Search as a Matheuristic for the Multi-Mode Resource-Constrained Project Scheduling Problem
by Patrick Gerhards, Christian Stürck, Andreas Fink
Abstract: The multi-mode resource-constrained project scheduling problem is a well known problem in the field of scheduling. The objective of the problem is to find the minimum makespan for the project. Hence, each activity has to be assigned to a mode and a starting time. At the same time, precedence and resource constraints must not be violated. We present a hybrid approach which combines an adaptive large neighborhood search with mixed integer programming. We applied the procedure to datasets from the MMLIB library with up to 100 activities and 9 modes. The computational results show that the approach is competitive with other state-of-the-art heuristics. Moreover, it found 294 new best known solutions and outperformed all other published methods on the MMLIB+ dataset.
Keywords: MRCPSP; Multi-mode resource-constrained project scheduling problem; Matheuristic; Adaptive large neighborhood search; MMLIB.
Solution algorithms to minimize the total family tardiness for job shop scheduling with job families
by Jae-Min , Dong-Ho Lee
PSO and Simulated annealing for the two machines flowshop scheduling problem with coupled-operations
by Nadjat Meziani, Mourad Boudhar, Ammar Oulamara
The Total Adjustment Cost Problem with Variable Activity Durations and Intensities
by Massimiliano Caramia
Abstract: Resource levelling is a crucial problem in project management since excessive peaks of resource usage in a schedule may cause additional costs, e.g., related to the need of relying on external resources. In this paper, we study the resource levelling problem with the so called total adjustment cost objective which has been more considered recently in the literature than others. For this problem, we propose a mixed-integer program in which, besides standard ingredients, variable durations and variable execution intensities of the activities are allowed to further smooth the shape of the resource profile function over time. A computational experimentation on known benchmarks has been conducted. Moreover, a comparison with a competing
Keywords: Project scheduling; Generalized precedence relationships; Resource levelling; Variable execution intensities.
Multi-Objective Binary Cuckoo Search for Constrained Project Portfolio Selection Under Uncertainty
by Mohammed El-Kholany
Abstract: One of the recurrent complex decisions faced by organisations is Project Portfolio Selection (PPS) in which a group of the most beneficial projects must be selected from a set of candidate projects. Accordingly, effective means for selecting projects must be employed in order for the organisation to survive in today
Keywords: Project Portfolio Selection; Cuckoo Search Algorithm; Simulation Based Optimization; Non-Dominated Cuckoo Search.
Forecast-corrected production-inventory control policy in unreliable manufacturing systems
by Nan Li, Felix T.S. Chan, S.H. Chung
Abstract: In traditional research on production-inventory control problems with failure-prone manufacturing systems, a stationary demand process is an essential assumption. However, such a situation may not be true. This study extends the hedging-point-based production-inventory control problem into the case with non-stationary demand. The demand forecasting process is simulated and categorised into two different cases. First of all, a two-level control policy is proposed to solve the problem with a Markov modulated Poisson demand process which is often used in qualitative forecasting. Then the quantitative forecasting process using time series methods is modelled and a forecast-corrected control policy is proposed accordingly. The impact of forecasting on the system performance is then investigated. An integrated simulation and experimental design method was adopted to solve the modified optimal control problem. The results show that the proposed control policy can outperform the traditional stationary policy when the forecasting error is limited to a certain level. [Received 29 August 2014; Revised 13 July 2015; Revised 12 April 2016; Revised 20 September 2016; Revised 21 September 2016; Accepted 30 March 2017]
Keywords: supply chain; production control; inventory control; forecasting; simulation; optimisation.
Manufacturing quality improvement and setup cost reduction in a vendor-buyer supply chain model
by Arunava Majumder, Rekha Guchhait, Biswajit Sarkar
Abstract: Quality improvement and setup cost reduction of any production system are endless procedure. Customer's demand is always intended to have the best quality product and the industries always try to improve the quality of products. This paper develops a two-echelon supply chain model with quality improvement of products and setup cost reduction under controllable lead time. The lead time demand follows a normal distribution and in the second case, it does not consider any specific distribution except a mean and standard deviation. Both models are solved analytically to obtain global solution. Two improved iterative algorithms are developed in order to obtain the optimal results of decision variables numerically to minimise the total system cost. The expected value of additional information is calculated to show the financial effect for collecting the information about lead time demand distribution. Some numerical examples and sensitivity analysis are given to illustrate the model. [Received 8 December 2016; Revised 27 March 2017; Accepted 21 April 2017]
Keywords: supply chain management; SCM; vendor's setup cost reduction; manufacturing quality improvement; distribution free approach.
An approach for rush order acceptance decisions using simulation and multi-attribute utility theory
by Faisal Aqlan, Abdulaziz Ahmed, Omar Ashour, Abdulrahman Shamsan, Mohammad M. Hamasha
Abstract: Rush orders are orders with shorter lead times and higher operating priorities compared to regular orders. A company may accept rush order, regardless of its capacity or raw material constraints, to maintain customer satisfaction and/or increase profit. On the other hand, rush orders can cause problems in managing production systems due to the unbalanced use of system resources. In this paper, discrete event simulation (DES) and multi-attribute utility theory (MAUT) are integrated to study the impact of rush orders on the performance of a hybrid push-pull production system. The proposed approach is used to identify the best acceptance levels of rush orders. Numerical results showed that prioritising customer orders based on their associated utilities can improve the performance of a production system. In addition, the best acceptance levels of rush orders can be determined by maximising the performance of the production system while considering production constraints. [Received 25 May 2015; Revised 1 August 2016; Revised 6 September 2016; Revised 3 March 2017; Accepted 5 June 2017]
Keywords: rush orders; push-pull production system; discrete event simulation; DES; multi-attribute utility theory; MAUT.
A hybrid metaheuristic method for the deterministic and robust uncapacitated multiple allocation p-hub centre problem
by Stefan Miškovic, Zorica Stanimirovic
Abstract: This study considers the well-known uncapacitated multiple allocation p-hub centre problem (UMApHCP) and introduces its robust variant (UMApHCP-R) by involving flow variations with unknown distributions. As a solution method to both UMApHCP and UMAPHCP-R, a hybrid metaheuristic algorithm (HMA) is proposed, which successfully combines particle swarm optimisation and a local search heuristic. Constructive elements of the HMA are adapted to the considered problems and its parameters are experimentally adjusted. Experimental results obtained for the UMApHCP show the superiority of the proposed HMA over the existing methods from the literature on standard hub instances in the sense of solution quality or running times. The results obtained by the HMA on large-scale hub instances with up to 900 nodes are also presented. The analysis of the HMA results for the UMApHCP-R on selected problem instances shows the impact of flow variations on the objective function value. [Received 11 September 2016; Revised 23 March 2017; Accepted 7 July 2017]
Keywords: hub location problems; robust optimisation; metaheuristics; particle swarm optimisation; PSO; local search; hybrid optimisation method; transportation and telecommunication networks.
Impact of human factor on flexibility and supply chain agility of La Rioja wineries
by Jorge Luis García-Alcaraz, Aidé Aracely Maldonado-Macías, Giner Alor Hernandez, Emilio Jiménez-Macías, Juan Carlos Sáenz Diez Muro, Julio Blanco-Fernández
Abstract: Human factors play an important role in the success of companies, especially in the performance of production systems. In this research paper, we propose a structural equation model that measures the impact of four human factors (knowledge, abilities, skills, and availability) on production process flexibility and supply chain agility in the wine industry of La Rioja, Spain. The results obtained indicate that these human factors have a direct and positive impact on production process flexibility and supply chain agility. Likewise, they can be indirectly linked to supply chain agility through production process flexibility. Based on these findings, this research encourages La Rioja wineries to jointly work with viticulture and enology programs of Spanish universities. This collaboration would enhance the impact of human factors on the wine industry, which would in turn allow wineries to rapidly and more effectively respond to customer needs. [Received 6 November 2015; Revised 15 October 2016; Revised 7 March 2017; Accepted 10 July 2017]
Keywords: wineries; supply chain; human factors; supply chain agility; production process flexibility; La Rioja.
Lot-sizing policies for defective and deteriorating items with time-dependent demand and trade credit
by Sunil Tiwari, Hui-Ming Wee, Sumon Sarkar
Abstract: This study investigates an inventory model with unreliable supply where each received lot may have random fraction of defective items with known distribution. Thus, item inspection becomes essential in all the situations, especially when the items are of deteriorating nature. Moreover, in today's competitive business world, organisations may use promotional tools in order to increase their sales. One such tool is permissible delay in payments where the buyer does not have to pay for the goods purchased until a prescribed period given by the supplier. For the case when both the demand and the price vary with time, we investigate the impact on the retailer's ordering policy for deteriorating items under permissible delay in payments. Numerical examples and sensitivity analysis are illustrated to provide some important managerial implications. [Received 26 December 2016; Revised 20 April 2017; Revised 5 June 2017; Revised 3 July 2017; Accepted 11 July 2017]
Keywords: EOQ inventory model; deterioration; imperfect items; time-dependent demand; trade credit.