An interval programming based approach for fully uncertain resource-constrained project scheduling problem considering project manager's attitude toward risk

In recent years, there has been a growing attention to model and solve resource-constrained project scheduling problem (RCPSP) under uncertain environments. In most of the real-life cases, project managers may face with many uncertainties in activity durations, resource availabilities, resource requirements of the activities, the earliest and latest finishing times of the activities etc. In addition to these input parameters, project schedule which represents the starting and/or completion times of the activities should also be considered as uncertain variables in such a fully uncertain environments where all of the project data are imprecise. Based on this motivation, this paper presents an interval programming based transformation approach to overcome fully uncertain nature of the problem. In detail, classical discrete-time binary integer programming model of the deterministic problem was extended by incorporating interval-valued parameters and decision variables. Then, fully uncertain RCPSP was transformed into the crisp equivalent form by making use of interval programming, interval ranking and interval arithmetic operations. In the proposed approach, interval arithmetic operations are performed by using supplementary information obtained from the project manager. Thus, the proposed approach is also able to take into account the project managers' attitude toward risk and produces more acceptable and risk-free solutions. Finally, a real-life liquefied natural gas (LNG) storage tank construction project in a petroleum refinery is presented for testing its validity and practicality. The computational results have shown that more applicable and information efficient project schedules can be derived via the proposed approach according to the project manager's attitude toward risk

Kapalı çevrim tedarik zincirlerinde stratejik ve taktiksel planlama problemlerinin belirli ve bulanık ortamlarda modellenmesi

Günümüzde, çevresel, ekonomik konular ve yasal zorunluluklar nedeniyle Tersine Lojistik (TL) ve Kapalı Çevrim Tedarik Zinciri (KÇTZ) kavramları kapsamında yeniden imalat, geri dönüşüm ve yeniden kullanım gibi geri kazanım alternatiflerine artan ilgi görülmektedir. Bu doğrultuda, işletmeler hem stratejik hem de taktiksel düzeyde aktivitelerini planlarken kullanılan geri kazanım opsiyonunu dikkate almalıdırlar. Öte yandan, literatürde stratejik planlama düzeyinde yer alan TL ve KÇTZ ağ tasarım problemine ilişkin birçok çalışma bulunmasına karşın, bunlardan çok azı taktiksel planlamayı konu edinmektedir. Ayrıca, literatürde çok amaçlı TL ve KÇTZ ağ tasarım modellerinin sayısı da sınırlıdır. Literatürdeki bu boşlukları gidermek üzere Model I, II ve III olmak üzere üç farklı matematiksel model önerilmiştir. Model I, bir kurşun/asit akü KÇTZ'ne ilişkin ağ tasarım problemi için bulanık ortamda geliştirilmiş çok amaçlı, çok aşamalı ve çok ürünlü karma tamsayılı programlama modelidir. Daha evvel ele alınmamış bir amaç (açılan tesisler tarafından toplanacak kullanılmış akü miktarının en büyüklenmesi) literatürde iyi bilinen en büyük kapsama problemine dayanılarak ele alınmıştır. Model II, ömrünü tamamlamış lastiklere ilişkin KÇTZ'ndeki toplam karın en büyüklenmesi ve KÇTZ boyunca oluşan toplam çevresel etkinin en küçüklenmesini amaçlayan, birden çok geri kazanım alternatifini ve zaman periyodunu dikkate alan bütünsel stratejik planlama modelidir. Ayrıca, kavramsal bir ürüne ilişkin KÇTZ'ndeki orta dönem planlanma problemi için yeniden imalat opsiyonu dikkate alınarak bir bulanık karma tamsayılı programlama modeli (Model III) geliştirilmiştir. Gerçek hayattaki KÇTZ'leri birçok belirsizlikle çevrili olduğu için, kapasiteler, talepler, haftalık üretim/yeniden imalat süreleri, taşımalara ilişkin sınırlar, geri dönüşüm yüzdeleri ve geri dönen ürünler için kabul edilme oranları bulanık veri olarak ele alınmıştır. Nowadays, there has been a growing interest in recycling, remanufacturing and reusing in the scope of Reverse Logistics (RL) and Closed-Loop Supply Chain (CLSC) concepts due to environmental, economical issues and legal obligations. For this reason, companies should take into account utilized recovery option while preparing both strategic and tactical planning activities. On the other hand, there are lots of studies in literature related to the RL and CLSC network design problem which takes place in strategic planning level but a few of them handles the tactical planning processes. However, multi-objective RL and CLSC network design models are rarely discussed in the literature. For filling these gaps, three mathematical models; Model I, II and III are proposed. A multi-objective, multi-echelon and multi-product mixed integer linear programming Model I is developed for a lead/acid battery CLSC in fuzzy environment. An unhandled objective (maximize collection of spent batteries) is taken into account based on the well known maximal coverage problem. A holistic strategic planning Model II with two objectives; maximization of total CLSC profit and minimization of total environmental impact along the CLSC network is developed for a tire collection and recovery system considering multiple recovery options and time periods. A fuzzy mixed integer programming Model III is proposed for tactical planning in a CLSC related to a conceptual product with remanufacturing option. Since the real world CLSCs are surrounded with uncertainty, capacities, demands, return rates, acceptance ratios, available production/remanufacturing times, transportation upper bounds and objective function value are considered as fuzz

Çok amaçlı kurumsal kaynak planlaması uyarlama projelerinin insan kaynağı kısıtı ve belirsizlik altında çizelgelenmesi

Nowadays, there has been an increasing attention to enterprise resource planning (ERP) software implementation projects due to the rapid improvements in information technologies. In this context, project managers may face with several uncertainties during the project planning and scheduling phases. In this paper, scheduling of a multi-objective ERP implementation project is targeted under human resource constraints and uncertainty. Through the proposed interval programming based solution approach, uncertainties of the project parameters/inputs as well as the project schedules/outputs which represent the starting or completion times of the activities can be easily handled. Therefore, several alternative project schedules can be generated by making use of the proposed approach according to the risk appetite of the project managers. Additionally, efficiency and reliability factors of the human resources are also taken into account. Finally, computational results of a real-life application have shown that more applicable and reliable compromise solutions can be generated by the proposed approach considering both project makespan and effective utilization of the human resource capacities

An interval-stochastic programming based approach for a fully uncertain multi-objective and multi-mode resource investment project scheduling problem with an application to ERP project implementation

Most of the real-life project scheduling cases may involve different types of uncertainties simultaneously such as randomness, fuzziness and dynamism. Based on this motivation, the present paper proposes a novel interval programming and chance constrained optimization based hybrid solution approach for a fully uncertain, multi-objective and multi-mode resource investment project scheduling problem (MRIPSP). The classical discrete-time binary integer programming formulation of the problem is extended by incorporating both the interval-valued and interval-stochastic project parameters as well as variables. In addition to the uncertain project parameters/inputs, the completion times of the activities which represent the project schedule and the availabilities of the renewable project resources are also stated as uncertain project variables and represented by interval numbers. Then, the proposed interval-stochastic multi-mode resource investment project scheduling (IS-MRIPSP) model is converted into its crisp equivalent form by using the proposed approach. The proposed approach is also able to consider different types of project scheduling risks and produces more reliable and risk-free solutions according to the project manager's attitude toward risks. Furthermore, in addition to the classical makespan objective, effective and efficient utilization of the renewable project resources, i.e., human resources, is also targeted. The efficiency and reliability factors of the human resources are also taken into consideration. In order to generate balanced project schedules which tradeoffbetween the project time and total human resource costs, compromise programming approach is adapted. Finally, in order to test the validity and practicality of the proposed approach, a real-life application is presented for an enterprise resource planning (ERP) implementation project scheduling problem of an international industrial software company. (C) 2020 Elsevier Ltd. All rights reserved

Scheduling multi-objective enterprise resource planning implementation projects under human resource constraints and uncertainty

Nowadays, there has been an increasing attention to enterprise resource planning (ERP) software implementation projects due to the rapid improvements in information technologies. In this context, project managers may face with several uncertainties during the project planning and scheduling phases. In this paper, scheduling of a multi-objective ERP implementation project is targeted under human resource constraints and uncertainty. Through the proposed interval programming based solution approach, uncertainties of the project parameters/inputs as well as the project schedules/outputs which represent the starting or completion times of the activities can be easily handled. Therefore, several alternative project schedules can be generated by making use of the proposed approach according to the risk appetite of the project managers. Additionally, efficiency and reliability factors of the human resources are also taken into account. Finally, computational results of a real-life application have shown that more applicable and reliable compromise solutions can be generated by the proposed approach considering both project makespan and effective utilization of the human resource capacities