ILOG OPL Research Articles

An effective heuristic for the single-machine scheduling problem with flexible maintenance under human resource constraints

In this paper, we study a new scheduling problem that considers both production and flexible preventive maintenance on a single machine where the human resource constraints (the availability and the competence) are taken into account. The objective function involves both the tardiness and the earliness resulting from production and maintenance tasks. We propose a mathematical formulation of the studied problem that is expressed in the constraint programming (CP) paradigm as a set of linear constraints. This CP modeling had been implemented in ILOG OPL language and the exact method Cplex is applied on it to compute the optimal solutions of relatively small instances of the problem. Further, a heuristic algorithm is provided to deal with lager instances of the problem. Computational experiments demonstrate that the proposed heuristic performs well and is able to find good solutions to instances up to 700 jobs in a reasonable CPU time.

Resource scheduling based on energy consumption for sustainable manufacturing

The paper proposes an agent-based approach for measuring in real time energy consumption of resources in job-shop manufacturing processes. Data from industrial robots is collected, analysed and assigned to operation types, and then integrated in an optimization engine in order to estimate how alternating between makespan and energy consumption as objective functions affects the performances of the whole system. This study focuses on the optimization of energy consumption in manufacturing processes through operation scheduling on available resources. The decision making algorithm relies on a decentralized system collecting data about resources implementing thus an intelligent manufacturing control system; the optimization problem is implemented using IBM ILOG OPL.

Designing an environmentally conscious tire closed-loop supply chain network with multiple recovery options using interactive fuzzy goal programming

Significant environmental problems have been caused by the growth in the volume of used tires each year. In addition, remanufacturing and recycling options related to the end of life for tires are crucial issues at present because of difficulties related to the degradation of these scrap tires in the environment and the economic benefits of material and energy recovery. Thus, effective collection, storage, recycling, and appropriate disposal methods are required for used tires without damaging the environment by designing an efficient closed-loop supply chain network. Based on this motivation, we present a holistic modeling approach for a tire closed-loop supply chain using mixed integer linear programming. Alternative recovery options such as remanufacturing, recycling, and energy recovery are considered simultaneously in the model. The main objective of this study was to develop a multi-objective, multi-echelon, multi-product, and multi-period logistics network design model in a more holistic manner while also considering environmental issues. To quantify the environmental impact and the closed-loop supply chain, we used a life cycle assessment-based and damage-oriented method (eco-indicator 99). We applied the model to an illustrative case study and an interactive fuzzy goal programming approach was utilized to solve the proposed fuzzy multiple-objective network optimization model. In order to obtain the best profit values and to satisfy the environmental indicator targets, we examined the effects of some parameters (factors) within the profit and damage function using an experimental technique based on the Taguchi design. Experimental runs were conducted using the optimization solver in ILOG OPL Studio 6.3 and the results were evaluated based on Taguchi’s (S/N) ratios, analysis of means graphs, interaction graphs, and analysis of variance with MINITAB 14.

A fuzzy goal programming model to strategic planning problem of a lead/acid battery closed-loop supply chain

Economical, environmental and governmental considerations have forced the lead/acid battery manufacturers to build-up an effective and efficient spent battery collection and recovery systems. The design and implementation of such a collection and recycling system is affected by the distribution, collection and recycling facilities’ location decisions which are strategic and important. A fuzzy multi-objective, multi-echelon and multi-product mixed integer linear programming model with different importance and priorities are developed in this paper. In contrast to the existing multi-objective closed-loop supply chain network design models which are generally cost or profit oriented, a new objective namely “maximization of the collection of returned batteries covered by the opened facilities” is also taken into account. Since the lack of flexibility issues in most of the supply chain planning models, new flexibility objectives such as total recycling and collection volume flexibility are also introduced due to the nature of reverse flows. Fuzzy goal programming model with different importance and priorities is used to solve the developed model. Furthermore, a novel approach for obtaining the desirable achievement degree of each fuzzy goal is proposed based on “weighted geometric mean” for group decision making procedure in which the importance/weights and the index of optimism of each group member are different. The proposed model is applied to an illustrative example based on inspiration from the lead/acid industry in Turkey. Solution of the proposed model is achieved by using ILOG OPL Studio version 6.3. Sensitivity analysis of the proposed model is also presented by considering different scenarios.

열처리 공정의 생산스케줄 수립과 적용에 관한 연구

The purpose of this study is to formulate and solve the scheduling problem to heat-treatment process in forging process and apply it to industries. Heat-treatment is a common process in manufacturing heavy forged products in ship engines and wind power generators. Total complete time of the schedule depends on how to group parts and assign them into heat furnace. Efficient operation of heat-treatment process increases the productivity of whole production system while scheduling the parts into heat-treatment furnace is a combinatorial problem which is known as an NP-hard problem. So the scheduling, on manufacturing site, relies on engineers' experience. To improve heat-treatment process schedule, this study formulated it into an MIP mathematical model which minimizes total complete time. Three methods were applied to example problems and the results were compared to each other. In case of small problems, optimal solutions were easily found. In case of big problems, feasible solutions were found and that feasible solutions were very close to lower bound of the solutions. ILOG OPL Studio 5.5 was used in this study.

Fuzzy mixed integer programming model for medium-term planning in a closed-loop supply chain with remanufacturing option

Nowadays, there has been a growing interest in reverse logistics, recycling, remanufacturing and reusing due to the environmental, economical issues and legal obligations. Due to this fact, companies should take into account the remanufacturing option while preparing the medium term planning MTP activities instead of using traditional production planning models. There are lots of studies in the literature related to the reverse logistics RL and closed-loop supply chain CLSC network design problem which takes place in strategic planning level but a few of them handles the medium-term planning activities. Thus, a fuzzy mixed integer programming model for medium-term planning in a CLSC related to a conceptual product with remanufacturing option is developed in this paper. In the proposed model, both forward and reverse flows are included and two production alternatives are considered: either “production of new products directly in manufacturing plants” or “bringing the returned products back to 'as new condition' in the remanufacturing facilities”. However, real world closed-loop supply chains are surrounded with uncertainty. Thus, storage capacities, retailers' and wholesalers' demands, return rates, acceptance ratios, weekly available production/remanufacturing times, transportation upper bounds and objective function value are considered as fuzzy in the proposed model. The proposed fuzzy mathematical programming model is converted into a crisp equivalent model by utilizing several fuzzy aggregation procedures from the literature. The proposed model is applied to an illustrative case and scenario analysis is also carried out for evaluating the effects of some parameters related to the concerned collection-recovery system. Solution of the proposed model is achieved by using ILOG OPL Studio 6.3.

Modeling tactical planning decisions through a linear optimization model in sow farms

This paper deals with tactical planning decisions for breeding farms producing piglets through a linear optimization model. A medium-term planning horizon based on weekly periods is considered. The proposed model maximizes the profit of the farm and takes into account sow herd dynamics, housing facilities, reproduction management, available stocks and a target quota of a weekly number of farrowing to integrate piglet production into the pig supply chain management. As result, an optimal replacement policy of sows and a scheduling of purchases of gilts during the whole planning horizon are provided. The model is solved using the algebraic modeling language ILOG OPL 6.1 with CPLEX 11.2 as the linear optimization solver. The article also discusses results obtained from a sensitivity analysis performed to assess the suitability of the model approach and the benefits of representing real variability over time against time homogeneity. In addition, the analysis and results presented lead to better understand sow herd dynamics over a finite time-horizon and corresponding performance.

전시 최장 획득완료시간 최소화를 위한 복수 순회구매자 문제

In war time, minimizing the logistics response time for supporting military operations is strongly needed. In this paper, i propose the mathematical formulation for minimizing the maximal acquisition completion time in wartime or during a state of emergency. The main structure of this formulation is based on the traveling purchaser problem (TPP), which is a generalized form of the well-known traveling salesman problem (TSP). In the case of the general TPP, an objective function is to minimize the sum of the traveling cost and the purchase cost. However, in this study, the objective function is to minimize the traveling cost only. That's why it's more important to minimize the traveling cost (time or distance) than the purchase cost in wartime or in a state of emergency. I generate a specific instance and find out the optimal solution of this instance by using ILOG OPL STUDIO (CPLEX version 11.1).

Effiziente, operative Torbelegung mittels kombinatorischer Auktionen

Logistics Journal : Nicht-referierte Veröffentlichungen, Vol. 2008, Iss. März - Das operative Torbelegungsproblem (TBP) z. B. an einem Distributions- oder Cross-dockingzentrum ist ein logistisches Problem, bei dem es gilt, an- und abfahrende Fahrzeuge zeitlich und räumlich so auf die Warenein- und -ausgangstore zu verteilen, dass eine mög-lichst kostengünstige Abfertigung ermöglicht wird. Bisherige Arbeiten, die sich mit dem TBP beschäftigen, lassen Aspekte der Kooperation außer Acht. Dieser Beitrag stellt ein Verfahren vor, durch das der Nachteil einseitig optimaler Torbelegungen überwunden werden kann. Dabei wird auf das Mittel der kombinatorischen Auktionen zurückgegriffen und das TBP als Allokationsproblem modelliert, bei dem Frachtführer um Bündel konsekutiver Einheitszeit-intervalle an den Toren konkurrieren. Mittels eines Vickrey-Clarke-Groves-Mechanismus wird einerseits die Anreizkompatibilität, andererseits die individuelle Rationalität des Auk-tionsverfahrens sichergestellt. Das Verfahren wurde in ILOG OPL Studio 3.6.1 implemen-tiert und die durch Testdaten gewonnenen Ergebnisse zeigen, dass die Laufzeiten gering genug sind, um das Verfahren für die operative (kurzfristige) Planung einzusetzen und so transportlogistische Prozesse für alle Beteiligten wirtschaftlicher zu gestalten.

Constraint-Based Design in Participatory Housing Planning

We introduce some novel ideas for a constraint-based design strategy to support participatory housing planning processes in Latin America. The following lines intend to open the discussion on the requirements and effect of the computer implementation of a constraint satisfaction approach to solve elementary design problems in architectural practice. The case study applies to the building massing design problem posed by the Chilean urban regulatory framework that addresses single-family affordable houses. Two different implementation criteria are being tested in an ongoing series of trials providing further considerations. One prototype uses MAXON's CINEMA4D XPRESSO ® visual scripting environment to set up a semi-automated design environment which allows users to edit one feature-based 3D model of massing alternative at a time. The other prototype uses ILOG's OPL STUDIO ® constraint programming environment to achieve fully automated search and 2D visualization of all possible solution alternatives to separate subdomains of the building massing design problem.

CLP-Based project-driven manufacturing

This paper addresses decision-making support for project-driven design and manufacturing processes in small-and medium-size enterprises. The problem considered regards of finding of computationally effective approach aimed at scheduling of a new project subject to constraints imposed by a multi-project environment. In other words, we are looking for an answer whether a given production order specified by its cost and completion time can be accepted in a given manufacturing system specified by available production capability, i.e., the time-constrained resources availability. The problem belongs to a class of multi-mode case project scheduling problems, where the problem of finding a feasible solution is NP-complete. A CLP-based approach is proposed. Illustrative example of its application to a real-life company employing ILOG OPL Studio 3.6 software tool is presented.

A genetic algorithm for machine scheduling problem under shared resource constraints

In this paper, we present a popular machine scheduling problem with resource constraints in manufacturing engineering. A genetic algorithm based approach is put forward and illustrated, including a specialised encoding and two kinds of decoding greedy schemes. Compared with both several kinds of lower bounds we present in this paper and the results from ILOG OPL software package, it is shown that our rapid genetic algorithm achieved significant results with stable and near-optimal performance.

Generating two-terminal directed acyclic graphs with a given complexity index by constraint logic programming

Two-terminal directed acyclic graphs (st-dags) are used to model problems in many areas and, hence, measures for their topology are needed. Complexity Index ( CI) is one such measure and is defined as the minimum number of node reductions required to reduce a given st-dag into a single-arc graph, when used along with series and parallel reductions. In this research we present a constraint logic programming algorithm (implemented in ILOG's OPL–– Optimization Programming Language) for the generation of st-dags with a given CI. To this end the complexity graph with a maximum matching of CI, the dominator tree, the reverse dominator tree and the st-dag are characterized by a set of constraints. Then a multi-phase algorithm is presented which searches the space described by the set of constraints. Finally, the computational performance of the algorithm is tested.