Ali Cheaitou

Supplier selection and order allocation with green criteria

Green and traditional criteria for supplier selection were split into two sets.Two bi-objective and one multi-objective optimization models were proposed.The models use a combination of three tools: AHP, Fuzzy TOPSIS and optimization.The results show that the proposed approach is more flexible than the existing ones. This research provides a decision-making tool to solve a multi-period green supplier selection and order allocation problem. The tool contains three integrated components. First, fuzzy TOPSIS (technique for order of preference by similarity to ideal solution) is used to assign two preference weights to each potential supplier according to two sets of criteria taken separately: traditional and green. Second, top management uses an analytic hierarchy process (AHP) to assign a global importance weight to each of the two sets of criteria based on the strategy of the company and independently of the potential suppliers. Third, for each supplier, the preference weight obtained from fuzzy TOPSIS regarding the traditional criteria is then multiplied by the global importance weight of the set of traditional criteria. The same is done for the green criteria. The two combined preference weights obtained for each supplier are then used in addition to total cost to select the best suppliers and to allocate orders using multi-period bi-objective and multi-objective optimization. The mathematical models are solved using the weighted comprehensive criterion method and the branch-and-cut algorithm. The approach of this research has a major advantage: it provides top management with flexibility in giving more or less importance weight to green or traditional criteria regardless of the number of criteria in each category through the use of AHP, which reduces the effect of the number of criteria on the preference weight of the suppliers. Contrary to the case in which each supplier is evaluated on the basis of all criteria at the same time, the proposed approach would not necessarily result in a supplier with poor green performance being ranked among the best for a situation in which the number of green criteria is smaller than the number of traditional criteria. In this case, the final ranking would mainly depend on the global weight of the green criteria set given by the top management using AHP as well as on the ranking of the supplier in terms of green criteria obtained from fuzzy TOPSIS. Extensive numerical experiments are conducted in which the bi-objective and multi-objective models are compared and the effect of the separation between green and traditional criteria is investigated. The results show that the two optimization approaches provide very close solutions, which leads to a preference for the bi-objective approach because of its lower computation time. Moreover, the results confirm the flexibility of the proposed approach and show that combining all criteria in one set is a special case. Finally, a time study is performed, which shows that the bi-objective integer linear programming model has a polynomial computation time.

Liner shipping service optimisation with reefer containers capacity: an application to northern Europe–South America trade

Increasing the number of vessels in a container liner service while reducing speeds, known as slow steaming strategy, has been a short-term response since 2008 to the challenges of over-capacity and the rise in bunker prices faced by shipping lines. This strategy, which reduces the fuel cost per voyage but increases the operating costs as more vessels are added to the service, is difficult to sustain when the transit time significantly affects the transportation demand. This article proposes a model applied to this situation, referred to as a case of optimal speed under semi-elastic demand, for which containerised perishable product transport is sensitive to time, while frozen and dry products are not. It investigates if slow steaming is still optimal when working to maximise the total profit on the cycle. In order to demonstrate the proposed model, a numerical application is carried out for a direct Northern Europe to East Coast of South America container service, a route selected due to the high volume of fresh products. For this application, the speed that maximises the total profit with inelastic and semi-elastic demand is then estimated for several bunker fuel prices.

Green supplier selection and order allocation using an integrated fuzzy TOPSIS, AHP and IP approach

This paper proposes a model to solve an integrated green supplier selection and order allocation multi-period problem. The model consists of three stages; first stage uses fuzzy TOPSIS to rank and assign preference weights to a set of traditional and green criteria. Moreover, in the second stage, the criteria are grouped into two subsets, traditional and green, and then AHP is used to assign importance weights to each subset. The outputs of the first and second stage are used as an input for a bi-objective optimization model. The model assumes a deterministic demand. It also allows for shortage while ensuring that total demand will be satisfied at the end of the planning horizon even if with some delay. Comprehensive Criterion Method (CCM) is adopted to solve the bi-objective optimization and LINGO software is used to find the optimal solution.

Two-stage flexible supply contract with payback and information update

In this paper, we consider a two-stage supply contract model for advanced reservation of capacity, with payback option at the beginning of the selling season. Between the two decision stages, external information is collected that serves to update the demand forecast and permits to adjust the decisions of the first stage by exercising options or by returning some units to the supplier. The demand occurs during a single selling period. At the end of the period, the remaining inventory, if any, is sold at a salvage value. During the selling season, any satisfied demand is charged with a unit selling price and any unsatisfied demand is lost. The objective of the model is to determine the quantities to be ordered before the beginning of the selling season which can be interpreted as the amount of capacity to be reserved, in order to satisfy optimally the demand.

Dynamic green supplier selection and order allocation with quantity discounts and varying supplier availability

Abstract This paper aims to solve a multi-period green supplier selection and order allocation problem with all-unit quantity discounts, in which the availability of suppliers differs from one period to another. The proposed approach involves three stages. In the first stage, decision makers use fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to assign two preference weights to every potential supplier based on the suppliers performance in two sets of criteria considered separately: traditional and green. In the second stage, top management uses the analytic hierarchy process to assign an importance weight to each of the two sets of criteria based on the organizations strategy. The outputs of the first and second stages serve as inputs for a single-product bi-objective integer linear programming model with deterministic demand that takes into account all-unit quantity discounts and a varying number of suppliers in each period of the planning horizon. We implement the proposed mathematical model in MATLAB R2014a software using the weighted comprehensive criterion method and the branch-and-cut algorithm. Statistical analysis helps determine the most suitable ranking approach for suppliers when their availability changes in each period. This paper presents a numerical comparison between two settings: the first considers all-unit quantity discounts, and the second does not. Moreover, a time study shows that the proposed bi-objective integer linear programming model has an exponential computation time.

A Newsvendor Model with Initial Inventory and Two Salvage Opportunities

In this paper, we develop an extension of the newsvendor model with initial inventory. In addition to the usual quantity ordered at the beginning of the horizon and the usual quantity salvaged at the end of the horizon, we introduce a new decision variable: a salvage opportunity at the beginning of the horizon, which might be used in the case of high initial inventory level. We develop the expression of the optimal policy for this extended model, for a general demand distribution. The structure of this optimal policy is particular and is characterized by two threshold levels. Some managerial insights are given via numerical examples.

Greening of maritime transportation: a multi-objective optimization approach

This article is motivated by growing concerns related to shipping

Green Traveling Purchaser Problem model: A bi-objective optimization approach

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